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Small Police Agency Use of Social Media: Positive and Negative Outcomes Noted in a Case Study

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Xiaochen Hu, Nicholas P Lovrich, Small Police Agency Use of Social Media: Positive and Negative Outcomes Noted in a Case Study, Policing: A Journal of Policy and Practice , Volume 15, Issue 2, June 2021, Pages 1584–1599, https://doi.org/10.1093/police/paz077

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Many studies on police use of social media focus on large police agencies. The current case study investigates how a rather small police agency has attracted broad attention on ‘Facebook’. By selecting a relatively small police agency that received a great many Facebook ‘likes’, the study investigates two social media-centered questions: (1) What are this police agency’s strategies of engaging so many citizens on Facebook? and (2) what are potential risks related to these strategies? Findings suggest that two major strategies were used to achieve such uncommon ‘subscriber success’ on Facebook: (1) maintaining the department’s Facebook page as a personal account page directed towards a Chief’s or Sheriff’s own philosophy of policing and (2) writing Facebook posts in a folksy vernacular featuring slang terms and relating humorous (often suspect deprecating) stories using such language. The current study proposes that law enforcement agencies may use informal communication to engage citizens, but they also need a formal team to give consistency and avoid dependency on a single person regarding managing their Facebook accounts. Burgoon’s (1978) expectancy violations theory is used to help explain both the positive and negative outcomes noted in the current study. The principal public policy implications regarding social media use by police agencies are discussed, along with implications for further research.

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The Use of Social Media in Intelligence and Its Impact on Police Work

• First Online: 08 December 2020

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• Francis Fortin   ORCID: orcid.org/0000-0003-3642-2267 6 ,
• Julie Delle Donne 6 &
• Justine Knop 6  

Part of the book series: Palgrave's Critical Policing Studies ((PCPS))

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Digital platforms such as Facebook, Twitter, LinkedIn, or Instagram are now among the main tools for personal and professional communications. This has created a new relationship between privacy and visibility, as a large amount of personal information has become publicly accessible. Social media is now an indispensable tool in police work, especially in surveillance and intelligence gathering and when conducting investigations (Fallik et al., International Journal of Police Science & Management , 146135572091194, 2020). This chapter presents a summary of studies that have dealt with the topic of how social media is used in criminal intelligence work, focusing on the impact of social media and the challenges and opportunities associated with it. We look in particular at studies that deal with cases where social media was used to produce criminal intelligence and discuss the implications of the use of SOCMINT (social media intelligence).

We have no conflicts of interest to declare.

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Introduction: The Police and Social Media

Social Media Intelligence (SOCMINT)

An Analysis of UK Policing Engagement via Social Media

Aghababaei, S., & Makrehchi, M. (2016, October). Mining social media content for crime prediction. In 2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI) (pp. 526–531). IEEE.

Google Scholar  

Antonius, N., & Rich, L. (2013). Discovering collection and analysis techniques for social media to improve public safety. The International Technology Management Review, 3 (1), 42–53. https://doi.org/10.2991/itmr.2013.3.1.4 .

Article   Google Scholar  

Awan, I. (2014). Islamophobia and Twitter: A typology of online hate against Muslims on social media. Policy & Internet, 6 (2), 133–150.

Back, L. (2002). Aryans reading Adorno: Cyber-culture and twenty-first century racism. Ethnic and Racial Studies, 25 (4), 628–651.

Balasuriya, L., Wijeratne, S., Doran, D., & Sheth, A. (2016, August). Finding street gang members on Twitter. Article presented at the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, San Francisco, USA. Retrieved from https://arxiv.org/pdf/1610.09516.pdf .

Bartlett, J., Miller, C., Crump, J. et Middleton, L. (2013). Policing in an Information Age. Demos , 1–42.

Bennett, C. J., Haggerty, K. D., Lyon, D., & Steeves, V. (2014). Vivre à nu : La surveillance au Canada . Athabasca University Press.

Berger, J. M., & Strathearn, B. (2013, March). Developments in radicalisation and political violence. who matters online: Measuring influence, evaluating content and countering violent extremism in online social networks . Retrieved from http://icsr.info/wp-content/uploads/2013/03/ICSR_Berger-and-Strathearn.pdf .

Bérubé, M., Tang, U, Fortin, F., Ozalp, Williams, M., & Burnap, P. (in press). Social media forensics applied to assessment of post–critical incident social reaction: The case of the 2017 Manchester Arena bombing. Forensic Science International, 0,0.

Blanquart, G., & Cook, D. M. (2013, December). Twitter influence and cumulative perceptions of extremist support: A case study of geert wilders. Article presented at the 4 th Australian Counter Terrorism Conference, Perth, Australia. Retrieved from http://ro.ecu.edu.au/cgi/viewcontent.cgi?article=1021&context=act .

Boyd, D., & Ellison, N. B. (2008). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13, 210–230.

Brainard, L., & Edlins, M. (2015). Top 10 U.S. municipal police departments and their social media usage. The American Review of Public Administration , 45 (6), 728–745. https://doi.org/10.1177/0275074014524478 .

Brodeur, J.-P. (2006). Le renseignement: Distinctions préliminaires. Canadian Journal of Criminology and Criminal Justice . https://doi.org/10.3138/cjccj.47.1.15 .

Burnap, P., Rana, O. F., Avis, N., Williams, M., Housley, W., Edwards, A., et al. (2015). Detecting tension in online communities with computational Twitter analysis. Technological Forecasting and Social Change, 95, 96–108.

Burnap, P., & Williams, M. L. (2015). Cyber hate speech on Twitter: An application for machine classification and statistical modeling for policy and decision making. Policy & Internet, 7 (2), 233–242.

Burnap, P., & Williams, M. L. (2016). Us and them: Identifying cyber hate on Twitter across multiple protected characteristics. EPJ Data Science, 5 (11), 1–15.

Camargo, J. E., Torres, C. A., Martinez, O. H., & Gomez, F. A. (2016, September). A big data analytics citizens’ perception of security. Article presented at the 2016 IEEE International Smart Cities Conferences (ISC2), Trento, Italy. Retrieved from http://ieeexplore.ieee.org/document/7580846/ .

Carter, D. L. (2009). Law enforcement intelligence: A guide for state, local, and tribal law enforcement agencies (2nd ed.). Retrieved from: https://fas.org/irp/agency/doj/lei.pdf .

Cohen, K., Johansson, F., Kaati, L., & Mork, J. C. (2014). Detecting linguistic markers for radical violence in social media. Terrorism and Political Violence, 26 (1), 246–256.

Coyne, J. (2014). The role of strategic intelligence in law enforcement: Policing transnational organized crime in Canada, the United Kingdom and Australia . New York: Springer.

Coyne, J. W., & Bell, P. (2011). The role of strategic intelligence in anticipating transnational organised crime: A literary review. International Journal of Law, Crime and Justice, 39 (1), 60–78.

Delle Donne, J., & Fortin, F. (2018). Innovation and policing: Factors influencing the adoption of social medias by members of Quebec police organizations. Policing: A Journal of Policy and Practice . https://doi.org/10.1093/police/pay079 .

Denef, S., Kaptein, N., Bayerl, P. S., & Ramirez, L. (2012). Best practice in police social media adaptation . EU Project COMPOSITE .

Dupont, B. (2004). La technicisation du travail policier: Ambivalences et contradictions internes. Criminologie, 37 (1), 107–126. https://doi.org/10.7202/008719ar .

Edwards, A., Housley, W., Williams, M., Sloan, L., & Williams, M. (2013). Digital social research, social media and the sociological imagination: Surrogacy, augmentation and re-orientation. International Journal of Research Methodology, 16 (3), 245–260.

Estellés-Arolas, E. (2020). Using crowdsourcing for a safer society: When the crowd rules. European Journal of Criminology, First Published April 23, https://doi.org/10.1177/1477370820916439 .

Faith, T., & Bekir, C. (2015). Police use of technology to fight against crime. European Scientific Journal, 11 (10), 286–296.

Fallik, S. W., Deuchar, R., Crichlow, V. J., & Hodges, H. (2020). Policing through social media: A qualitative exploration. International Journal of Police Science & Management , 146135572091194. https://doi.org/10.1177/1461355720911948 .

Frank, R. G., & Cheng, C. (2011). Social media sites: New fora for criminal, communication, and investigation opportunities . https://www.semanticscholar.org/paper/Social-Media-Sites%3A-New-Fora-for-Criminal%2C-and-Frank-Cheng/ba46587e7f21b726a92aae47eed216d50462d0c0 .

Frank, R., Cheng, C., & Pun, V. (2011). Social media sites: New fora for criminal, communication, and investigation opportunities . Ottawa, ON: Public Safety Canada.

Ghajar-Khosravi, S., Kwantes, P., Derbentseva, N., & Huey, L. (2016). Quantifying salient concepts discussed in social media content: A case study using Twitter content written by radicalized youth. Journal of Terrorism Research, 7 (2), 79–90.

Graham, R. (2016). Inter-ideological mingling: White extremist ideology entering the mainstream on Twitter. Sociological Spectrum, 36 (1), 24–36.

Hadlington, L., Lumsden, K., Black, A., & Ferra, F. (2018). A qualitative exploration of police officers’ experiences, challenges, and perceptions of cybercrime. Policing: A Journal of Policy and Practice . https://doi.org/10.1093/police/pay090 .

HMIC. (2011). The rules of engagement: A review of the August 2011 disorders . London: HMIC.

Hofmann, R., & Feltes, T. (2020). Social media for community oriented policing: Best practices from around the world and future challenges. European Law Enforcement Research Bulletin Nr. 18 (Winter 2019).

Horsman, G., Ginty, K., & Cranner, P. (2017). Identifying offenders on Twitter: A law enforcement practitioner guide. Digital Investigation, 23, 63–74.

International Association of Chiefs of Police. (2017). 2016 Law enforcement use of social media survey . From: http://www.theiacp.org/Portals/0/documents/pdfs/2016-law-enforcement-use-of-social-media-survey.pdf .

Joseph, K., Wei, W., & Carley, K. M. (2017, February). Girls rule, boys drool: Extracting semantic and affective stereotypes from Twitter. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (pp. 1362–1374).

Krizan, L. (1999). Intelligence essentials for everyone . Washington, DC: Joint Military Intelligence College.

Kumar, A. S., & Singh, S. (2013). Detection of user cluster with suspicious activity in online social networking sites . 2013 2nd International Conference on Advanced Computing, Networking and Security, 220–225. https://doi.org/10.1109/ADCONS.2013.17 .

Lane, J., Ramirez, F. A., & Pearce, K. E. (2018). Guilty by visible association: Socially mediated visibility in gang prosecutions. Journal of Computer-Mediated Communication, 23 (6), 354–369. https://doi.org/10.1093/jcmc/zmy019 .

Leman-Langlois, S. (2013). Technocrime : technology, crime and social control . New York: Routledge.

Lemieux, F. (2008). Vers un renseignement criminel de qualité. Traité de sécurité intérieure , 290–299.

Marsico, E. M., Jr. (2009). Social networking websites: Are MySpace and Facebook the fingerprints of the twenty-first century? Widener LJ, 19, 967.

Martin, G. (2018). Crime, media and culture . New York, NY: Routledge.

McKeown, S., Maxwell, D., Azzopardi, L., & Glisson, W. B. (2014, August). Investigating people: A qualitative analysis of the search behaviours of open-source intelligence analysts. In Proceedings of the 5th Information Interaction in Context Symposium (pp. 175–184).

Moore, K. (2020). The use and effectiveness of law enforcement social media sites . Master: University of Oklahoma.

Murphy, J. P., & Fontecilla, A. (2013). Social media evidence in government investigations and criminal proceedings: A frontier of new legal issues. Richmond Journal of Law and Technology, 19 (3), 1–30.

Newnham, J., & Bell, P. (2012). Social network media and political activism: A growing challenge for law enforcement. Journal of Policing, Intelligence and Counter Terrorism, 7 (1), 36–50.

Omand, D., Bartlett, J., & Miller, C. (2012a). Introducing social media intelligence (SOCMINT). Intelligence and National Security, 27 (6), 801–823. https://doi.org/10.1080/02684527.2012.716965 .

Omand, D., Bartlett, J., & Miller, C. (2012b). A balance between security and privacy online must be stuck (Demos) . London.

ONUDD. (2010). Criminal intelligence. Manual for front-line law enforcement . 1–58. Available : http://www.unodc.org/documents/organized-crime/Law-Enforcement/Criminal_Intelligence_for_Front_Line_Law_Enforcement.pdf .

Oostdijk, N., & Van Halteren, H. (2013). Shallow parsing for recognizing threats in Dutch tweets . Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 1034–1041. https://doi.org/10.1145/2492517.2500271 .

Panagiotopoulos, P., Bigdeli, A. Z., & Sams, S. (2014). Citizen–government collaboration on social media: The case of Twitter in the 2011 riots in England. Government Information Quarterly, 31 (3), 349–357.

Procter, R., Crump, J., Karstedt, S., Voss, A., & Cantijoch, M. (2013). Reading the riots: What were the police doing on Twitter? Policing and Society, 23 (4), 413–436.

Purenne, A., & Wuilleumier, A. (2011). L’introduction des technologies de surveillance dans le travail policier. Facteur de changement ou de réassurance ? Droit et Cultures. Revue Internationale Interdisciplinaire, 61, 119–130.

Rainie, H., & Wellman, B. (2012). Networked: The new social operating system (Vol. 419). Cambridge, MA: Mit Press.

Rasheed, H., Khan, F. H., Bashir, S., & Fatima, I. (2019). Detecting suspicious discussion on online forums using data mining. In Dans I. S. Bajwa, F. Kamareddine, & A. Costa (Éds.), Intelligent technologies and applications (pp. 262–273). Springer. https://doi.org/10.1007/978-981-13-6052-7_23 .

Ratcliffe, J. (2009). Strategic thinking in criminal intelligence: 2nd edition . Sydney, Australia: Federation Press.

Renard, B. (2011). La technologie ADN dans la justice pénale : Une illustration de la recomposition de l’action de la justice par la science, la technique et l’expertise ? Droit et cultures. Revue internationale interdisciplinaire , 61 , Article 61. http://journals.openedition.org/droitcultures/2467 .

Reuter, C., Kaufhold, M. A., Spahr, F., Spielhofer, T., & Hahne, A. S. (2020). Emergency service staff and social media—A comparative empirical study of the attitude by emergency services staff in Europe in 2014 and 2017. International Journal of Disaster Risk Reduction , 46 (October 2018). https://doi.org/10.1016/j.ijdrr.2020.101516 .

Reyes, A., Rosso, P., & Veale, T. (2012). A multidimensional approach for detecting irony in Twitter. Language Resources & Evaluation, 47 (1), 239–268.

Rodriguez, R. M. J. (2014). A spatial analysis of Boko Haram and Al-Shabaab references in social media in Sub-Saharan Africa [Thesis]. http://mars.gmu.edu/handle/1920/9110 .

Scassa, T. (2017). Law enforcement in the age of big data and surveillance intermediaries: Transparency challenges. SCRIPT-Ed, 14 (2), 239–284. https://doi.org/10.2966/scrip.140217.239 .

Trottier, D. (2012). Policing social media. Canadian Review of Sociology/Revue Canadienne de Sociologie, 49 (4), 411–425. https://doi.org/10.1111/j.1755-618X.2012.01302.x .

Trottier, D. (2016). Social media as surveillance: Rethinking visibility in a converging world . Farnham: Ashgate Press.

Walsh, J. P., & O’Connor, C. (2019). Social media and policing: A review of recent research. Sociology Compass, 13 (1), 1–14. https://doi.org/10.1111/soc4.12648 .

Weaver, S. (2013). A rhetorical discourse analysis of online anti-muslim and anti-semitic jokes. Ethnic and Racial Studies, 36 (3), 483–499.

Wei, W., Joseph, K., Liu, H., & Carley, K. (2016). Exploring characteristics of suspended users and network stability on Twitter. Social Network Analysis and Mining, 6 (51), 1–18.

Wu, S., Hofman, J. M., Mason, W. A. & Watts, D. J. (2011, March). Who says what to whom on Twitter. Article presented at the International World Wide Web Conference, Hyderabad, India. Retrieved from http://www.wwwconference.org/proceedings/www2011/proceedings/p705.pdf .

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Francis Fortin, Julie Delle Donne & Justine Knop

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Fortin, F., Delle Donne, J., Knop, J. (2021). The Use of Social Media in Intelligence and Its Impact on Police Work. In: Nolan, J.J., Crispino, F., Parsons, T. (eds) Policing in an Age of Reform. Palgrave's Critical Policing Studies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-56765-1_13

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Research Article

Reaching and engaging people: Analyzing tweeting practices of large U.S. police departments pre- and post- the killing of George Floyd

Roles Conceptualization, Data curation, Formal analysis, Methodology, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Criminology, Law and Society, George Mason University, Fairfax, VA, United States of America

Roles Conceptualization, Data curation, Writing – original draft, Writing – review & editing

Affiliation National Policing Institute, Arlington, VA, United States of America

• Beidi Dong, 

• Published: July 14, 2022
• https://doi.org/10.1371/journal.pone.0269288
• Reader Comments

Finding ways to improve police legitimacy and police-community relations has for long been an important social issue in the United States. It becomes particularly urgent following the murder of George Floyd on May 25 th , 2020. An emerging area that holds potential in remediating police-community relations pertains to the use of social media by police. Yet, this body of research stays highly exploratory (e.g., case studies based on a small sample of agencies) and different viewpoints exist regarding the objectives of police social media usage. The current study identified 115 large police departments in the U.S. and collected their tweets over a 4-month period between 4/1/2020 and 7/31/2020. We investigated how police agencies (both individually and as an aggregate) leveraged social media to respond to the nationwide protests directed at the police and community reactions to such responses. We found that police agencies tweeted more frequently in the immediate aftermath of the murder and posted an increased number of civil-unrest related tweets. The public showed a greater interest in engaging with law enforcement agencies (i.e., average favorite and retweet counts) following the murder. A great variability emerged across agencies in their responses on social media, suggesting that examining only a handful of agencies or a particular dimension of social media usage would limit our understanding of police behaviors and citizen interactions on social media. In conclusion, we suggested a few avenues for future research (and practices) on responsible and effective use of social media by police, while pointing out the challenges associated with such inquiries.

Citation: Dong B, Wu X (2022) Reaching and engaging people: Analyzing tweeting practices of large U.S. police departments pre- and post- the killing of George Floyd. PLoS ONE 17(7): e0269288. https://doi.org/10.1371/journal.pone.0269288

Editor: Rogis Baker, Universiti Pertahanan Nasional Malaysia, MALAYSIA

Received: January 4, 2022; Accepted: May 17, 2022; Published: July 14, 2022

Copyright: © 2022 Dong, Wu. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The study’s minimal underlying dataset was uploaded to a stable, public repository. Please see https://www.kaggle.com/datasets/bdresearch/pd-tmline .

Funding: The authors received no specific funding for this work.

Competing interests: Xiaoyun Wu is an employee of the National Policing Institute (formerly the National Police Foundation), a not-for-profit organization committed to conducting research, training, and technical assistance in policing. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Introduction

On May 25, 2020, George Floyd, a 46-year-old Black man arrested on suspicion of using a counterfeit $20 bill, was murdered by Derek Chauvin, a 44-year-old white police officer in the Minneapolis Police Department who knelt on Floyd’s neck for almost 10 minutes. Following the killing of George Floyd, the social protest movement across the United States (U.S.) in the summer of 2020 led to a new round of contentious debates on police work, with many calling for fundamental police reform (e.g., to “defund the police”) and enhanced accountability. Inquiries on ways to improve police legitimacy and police-community relations have not been more urgent, as law enforcement agencies continue to represent the primary source of social control and the public rely on them for protection in a turbulent social environment (e.g., the recent spike of homicides amidst an ongoing pandemic) [ 1 – 5 ].

An emerging area that holds potential in remediating police-community relations pertains to the use of social media by police [ 6 ]. Throughout the protests, we saw police departments across jurisdictions engaging in public conversations and other activities on social media, some of which garnered extensive public attention. Despite some preliminary evidence suggesting the potential benefits of a police presence on social media, research on police use of social media has been relatively scant, as well as mixed [ 7 – 10 ]. Advocates for increasing police presence on social media suggested a myriad of potential benefits, including improving community outreach, investigation, and crime prevention [ 11 , 12 ]. Inversely, police social media usage was argued to mainly fulfill a function of socialization (i.e., people internalize how police think and what police value) or legitimation (i.e., police justify contested actions through direct information sharing), thereby mediating public pressure for reform [ 13 ]. Additionally, there are concerns that police mostly engage in shallow, non-dialogical interactions with the public on social media [ 14 – 16 ].

In light of these dissimilar viewpoints of police social media usage, the current study seeks to understand how police in the U.S. leveraged social media to respond to the killing of George Floyd and to the nationwide protests that ensued. The study is motivated by 1) an increasing social media presence of law enforcement agencies [ 17 ], 2) ongoing frictions between police and disadvantaged and minority communities, 3) perceived benefits and challenges of social media usage among police practitioners, and 4) limited research covering police use of social media and its impact across the nation. The scale and intensity of the protest, amidst a global pandemic that ushered in a period of rapid growth in digital communication generally [ 18 ] and in policing [ 19 ], provide us with an exceptional opportunity to examine police social media usage and community reactions to it.

Police use of social media

Police presence on social media has become growingly prevalent in the U.S. and other countries over the past decade. In a recent law enforcement use of social media survey in the U.S., Kim and colleagues noted that about 96% of their agency respondents (N = 539) affiliated with the International Association of Chiefs of Police (IACP) have a social media account as of 2016, with most agencies adopting social media usage between 2010 and 2014 [ 17 ]. Social media is thought to also serve as a technological driver of open government initiatives. The Open Government Directive of the Obama administration propels government agencies to provide more information to the public and to establish mechanisms through which public feedback can be collected and used to evaluate and improve government performance [ 9 , 20 , 21 ]. This trend continues to be facilitated by the COVID-19 pandemic, which has prompted digitization of government communications and transactions at an unprecedented rate and urged many police agencies to shift their community engagement activities online through social media platforms [ 19 ].

As a direct communication channel, social media allows the police to bypass traditional news media and reach a wider audience at a low cost and with greater efficiency [ 22 , 23 ]. Policing scholarship has established that law enforcement agencies commonly seek to gather intelligence, enhance crime prevention and investigation, humanize the agency, engage in image-building activities, and improve their relations with the public through social media usage, which are consistent with the overall goals of community-oriented policing [ 11 , 14 , 24 , 25 ]. At times of immediate crisis, police social media usage has the advantages over traditional news outlets to deliver instant messages to the mass. By exerting authority and providing immediate responses under exceptional circumstances, police agencies’ social media accounts often become the trusted source for information and can garner wide societal attention. Such instances were found during natural disasters, demonstration and social riots, terrorist attacks, among others [ 8 , 26 – 28 ].

Nonetheless, the actual impact of social media usage in transforming police work and remediating police-community relations well depends on the way in which police agencies use it. Prior research suggests a variability across law enforcement agencies in social media usage, depending on agency organizational goals and pre-existing communication strategies [ 9 ]. This may be particularly evident in crisis situations. The crisis communication literature suggests that image-making and repair are one main motivation behind individual or organizational responses to crises [ 29 ]. Image is considered threatened when an organization or individual has committed or was responsible for an offensive act. Specifically, image repair theory identifies several approaches in response to accusations or damages including denial, evasion of responsibility (e.g., provocation, defeasibility, accident, or good intentions), reducing offensiveness of event (e.g., bolstering, minimization, differentiation, etc.), and mortification and corrective action attempt to repair an image without directly dealing with blame or offensiveness [ 30 ].

While social media may be used to promote a more open culture in police departments [ 31 ], social media platforms such as Twitter may also be used to publicize police-curated content unfiltered by traditional mass media, serving the purposes of deflecting institutional change (e.g., through socialization and/or legitimation) and mediating public pressure for reform. In a case study examining the New York Police Department (NYPD)’s daily Twitter posts in 2018 and an in-depth analysis of public reactions on Twitter to a contested NYPD shooting (i.e., the killing of Saheed Vassell), Cheng concluded that police social media usage represents “selective transparency” and mainly provides police with the technological capacity to “shape social memories while avoiding various forms of public accountability” (p.413) [ 13 ]. In the case of George Floyd, police as a profession have received heavy criticism for the long-standing racial disparities in policing outcomes and a string of fatal encounters between police and black citizens in recent years (e.g., Michael Brown, Freddie Gray, Breonna Taylor, etc.). As such, most U.S. police agencies would feel compelled to respond to the killing of George Floyd and associated protest activities through an image repair angle (e.g., emphasizing their role in fighting crime to ease public outrage or devoting an increased share of social media posts to racial justice related posts as a corrective action).

Current study

The bulk of research on police use of social media has emerged within the past decade, scattered in such areas as criminology, sociology, public administration, communication, and information technology. It is far from clear what constitutes responsible and effective police public engagement on social media and whether actual uses of social media by police live up to the ideal of a community-oriented policing approach or mainly serve self-interested purposes [ 14 , 16 , 32 , 33 ]. This body of research stays highly exploratory and is conducted typically on a small sample of agencies that limits their generalizability [ 7 , 24 , 33 – 35 ]. Narrowing this research gap has important implications to the study of innovative, sustainable ways through which police improve their engagement with targeted groups and the broader audiences. Expanding research on police use of social media also propels understanding of the utility (or lack thereof) of social media as a communication strategy for public or government agencies like law enforcement.

The current study seeks to examine how law enforcement agencies across the nation reacted on social media following a major legitimacy crisis. This inquiry is further situated within the context of a global pandemic that has pushed digital communication to the forefront. Specifically, we identified 115 large police departments in the U.S. with a regular presence on Twitter. We collected their tweets over a 4-month period between 4/1/2020 and 7/31/2020, covering critical periods before and after the killing of George Floyd and the nationwide protests that followed. With this, we aim to understand whether and how police agencies (both individually and as an aggregate) leveraged social media to respond to the social protests directed at the police. By combining a host of items that capture police activities on social media and public reactions to their activities, we created a single index to indicate how well police agencies engaged (or governed in a more neutral sense) the public on Twitter during the George Floyd protests.

Materials and methods

Data and sample.

Using the 2016 Law Enforcement Management and Administrative Statistics (LEMAS) survey [ 36 ], we identified 139 large law enforcement agencies in the U.S. with more than 300 sworn officers and serving a population of 300,000 people and more. We focus on large agencies because they are most likely to have a regular social media presence, thus providing sufficient social media posts for analysis. The screening criteria were used in efforts to attain a meaningful and manageable sample of large U.S. police departments. We located Twitter handles of 137 (out of 139) law enforcement agencies. For police agencies with multiple official Twitter accounts, we selected only the main account with the greatest number of followers (also tweets and replies). All tweets from these agencies were fetched through Twitter’s Application Programming Interface (API) using R package rtweet on August 25th, 2020 [ 37 ]. Twitter handles of each of the 137 law enforcement agencies were used in the get_timeline function. Our data collection method complied with Twitter’s terms and conditions. We set the study period from April 1st, 2020 to July 31st, 2020 (approximately two months before and after the killing of George Floyd). This four-month study period allowed us enough data to analyze police Twitter usage before and after the killing of George Floyd and lessened the influence of the onset of the COVID-19 pandemic on police presence on social media. We excluded law enforcement agencies posting fewer than 50 tweets (including replies but excluding retweets) during this period. The final analysis sample included 115 law enforcement agencies and 38,701 tweets over a 4-month period. A complete list of these law enforcement agencies is included in S1 Table .

It is worth noting that we only examined police use of Twitter in the study due to data availability constraints. Twitter reaches between one-fifths and one-quarter of the U.S. population, and its users are younger, more likely to identify as Democrats, more highly educated and have higher incomes than U.S. adults overall [ 38 ]. Thus, the findings should be interpreted with caution due to the non-coverage of other social media platforms used by law enforcement agencies (e.g., Facebook or Nextdoor) and the demographics of Twitter users.

Data analysis

Data analysis proceeded in three main steps. First, descriptive patterns were presented to show the frequency, public reactions (i.e., favorite and retweet counts), and emotions (characterized by pre-existing sentiment lexicon and metric) expressed in the tweets of the 115 large U.S. police departments before and after the killing of George Floyd. Second, a supervised machine learning algorithm was trained to categorize each of these tweets according to a 7-category scheme. The 7 categories are: 1) civil unrest related; 2) COVID-19 related; 3) police gathering of information; 4) police communication of administrative and mundane information; 5) police communication of traffic information; 6) police communication of case updates; and 7) community engagement and outreach. The categorization scheme was constructed based on previous studies of police social media usage, consultation of leading policing scholars and practitioners, and the focus of the current study [ 6 , 22 , 39 ]. Detailed categorization and exemplary tweets can be seen in S2 Table . Changes in the categories or focal issues of police departments tweets before and after the killing were analyzed. Specifically, to train the multiclass classifier, a random subset of 5,000 tweets were sampled and manually labeled into one of the 7 pre-defined categories. Each author independently labeled these tweets and the intercoder reliability was about 0.70. Discrepancies were identified, discussed, and resolved (i.e., agreement on the final categorizations). The random forest classifier was evaluated with the labeled tweets (with a 75/25 split) and then applied to the entire set of tweets for classification. Additional technical details can be found in S3 Table . Third, to assess adjustments of Twitter usage made by each of the 115 law enforcement agencies before and after the killing, we analyzed and ranked changes in the frequency, public reactions, and proportions of different categories of tweets. In addition, rankings for individual items were averaged to derive an overall ranking gauging police agencies’ performance on Twitter following the George Floyd protests. Data analysis was performed using R, version 4.0.2 in 2021.

Descriptive analysis of aggregate police tweets

Fig 1 shows that the 115 law enforcement agencies in our sample posted substantially more tweets in the week following the killing of George Floyd on May 25th, 2020. Yet, the number of tweets dropped to the pre-killing level after one week. Figs 2 and 3 present the average number of favorites and retweets received per tweet by the 115 law enforcement agencies before and after the killing. There was a noticeable increase in citizen reactions to police tweets immediately after the killing, and this trend lasted at least until the end of July 2020. To reduce the influence of “outliers”, tweets that received a favorite or retweet count exceeding three standard deviations above the mean were excluded. In the robustness check, substantively similar patterns were observed without excluding the outliers.

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Using the Bing sentiment lexicon—a widely used general purpose English lexicon that detects the sentiment of words through a dictionary lookup and classifies words as being “positive” or “negative” [ 40 ], Fig 4 shows that police-generated tweets during the study period were more likely to include words indicating a negative emotion than words expressing a positive emotion. The negative-to-positive words ratio further increased following the killing of George Floyd. Fig 5 depicts sentence-level emotional valence (i.e., the value associated with a stimulus as expressed on a continuum from pleasant to unpleasant or from attractive to aversive) in the tweets using Rinker’s sentimentr package. The package balances accuracy (e.g., considering valence shifters) and speed in calculating text polarity sentiment in the English language at the sentence level [ 41 ]. Consistent with Fig 4 , there was a decrease in the “pleasantness” or “attractiveness” expressed in the tweets over the study period. Exemplary tweets illustrating sentence-level pleasant or attractive versus unpleasant or aversive emotion can be seen in S4 Table .

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Focal issues of police tweets

Table 1 reports the accuracy and kappa of the multiclass random forest classifier. Ten-fold cross-validation indicates an overall accuracy of 0.814 and a kappa value of 0.767. When applying the classifier to the split test set, the accuracy was 0.808 and the kappa value equaled to 0.758, indicating a reasonably high accuracy. By-class accuracy was also acceptable for all sub-categories in cross-validation and when applying to the split test set. Supplementary details about the results of the multiclass random forest classifier can be found in S5 Table . With the trained classifier, 37,899 tweets were classified into the 7 pre-defined categories. The number of tweets reduced from 38,701 to 37,899 because text pre-processing removed tweets that only contained hyperlinks, digits/numbers, images, videos, or stop words. Table 2 shows the number of tweets by categories. Consistent with prior research, the most frequent categories were for community engagement and outreach purpose and for case updates.

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Fig 6 displays the proportions of focal issues mentioned in the tweets before and after the killing of George Floyd. There was a significant increase in the proportion of tweets related to civil unrest in the post-killing period and a significant decrease in the proportion of tweets that were COVID-19 related. More tweets were posted about case updates in the post-killing period, whereas fewer tweets were posted for community engagement and outreach purpose. Fig 7 further displays the distribution of police departments in relation to the changes in the focal issues of tweets. For instance, most police departments increased their posting of civil unrest related tweets (focal issue #1) and decreased the posting of COVID-19 related tweets (focal issue #2) in the post-killing period, whereas the distribution is more bell-shaped when looking at changes in tweets of community engagement and outreach (focal issue #7). Fig 8 shows public reactions by focal issues before and after the killing. The left panel shows that tweets related to civil unrest and community engagement and outreach received the highest average number of favorites per tweet. The pattern became more evident in the post-killing period. The right panel illustrates that tweets related to civil unrest and police gathering of information received the highest average number of retweets per tweet. Again, police audiences on Twitter were more likely to disseminate such information in the post-killing period.

Focal issues: (1) civil unrest related; (2) COVID-19 related; (3) police gathering of information; (4) police communication of administrative and mundane information; (5) police communication of traffic information; (6) police communication of case updates; and (7) community engagement and outreach.

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Adjustments of individual police departments Twitter usage

Tables 3 – 12 illustrate how each of the 115 law enforcement agencies adjusted their Twitter usage before and after the killing of George Floyd. To adjust for baseline levels of tweeting practices across police departments, the 115 law enforcement agencies were divided into two groups. Across the 115 law enforcement agencies, the mean was 155 and the median was 114 tweets in the pre-killing period. We made the cut-point at 110 tweets in the pre-killing period to create the two groups. The first group included the more active agencies, namely, the 60 agencies which posted, on average, at least 2 tweets per day during the pre-killing period (i.e., the higher-use group). The second group included the other 55 agencies which were less active on Twitter during the pre-killing period (i.e., the lower-use group). By dividing the agencies into the higher-use and lower-use groups, we balanced the raw and percentage changes when ranking the agencies and partially adjusted for potential influences of agency/personnel size and jurisdiction population (i.e., agency-level factors) on police social media usage.

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Tables 3 and 4 rank agencies in the higher- and lower-use group based on how substantially they increased or decreased their tweeting practices pre- and post-killing. For instance, the Aurora Police Department (ranked #1 in the higher-use group for this dimension) posted 152 tweets in the pre-killing period and 477 tweets in the post-killing period. The average number of posts per day was 2.76 (152 tweets/55 days) and 7.12 (477 tweets/67 days) pre- and post-killing. This translates to a raw frequency change of 4.36 (7.12–2.76) and a percentage change of 158% (7.12/2.76–1). Tables 5 and 6 rank the agencies based on the increase or decrease in the average number of favorites they received per tweet pre- and post-killing. For instance, tweets from the Venture County Sheriff’s Office (ranked #1 in the lower-use group for this dimension), on average, received 11.5 favorites in the pre-killing period and 139 favorites in the post-killing period, a raw favorite change of 127.5 (139–11.5) and a percentage change of 1117% (139/11.5–1). In a similar vein, Tables 7 and 8 rank the agencies based on the increase or decrease in the average number of retweets they received per tweet pre- and post-killing.

Moreover, Tables 9 and 10 rank the agencies based on the increase or decrease in posting civil unrest related tweets pre- and post-killing. For instance, the Portland Police Department (ranked #1 in the higher-use group for this dimension) posted a total of 303 tweets in the pre-killing period and none of the tweets were civil unrest related. Yet, in the post-killing period, they posted a total of 900 tweets, 535 of which were civil unrest related. Thus, the proportion change was 0.594 (535/900–0/303). Tables 11 and 12 rank the agencies based on the increase or decrease in posting community engagement and outreach tweets pre- and post-killing. For example, the NYPD (ranked #1 in the higher-use group for this dimension) posted a total of 663 tweets in the pre-killing period and 179 of the tweets were for community engagement and outreach purpose; in the post-killing period, they posted a total of 428 tweets, 205 of which were for community engagement and outreach purpose. Thus, the proportion change was 0.209 (205/428–179/663).

Finally, we combined the five dimensions above (Tables 3 through 12 ) and constructed an overall ranking to gauge which law enforcement agencies may have more effectively reached and engaged (or governed) citizens through Twitter. To offer a straightforward understanding, the five dimensions were assumed equal weights in our attempt and their corresponding ranks were averaged to derive an overall ranking. Tables 13 and 14 illustrate the overall rankings for the higher- and lower-use group. For example, the Charlotte-Mecklenburg Police Department (in the higher-use group) ranked 5 th in posting more tweets per day, 3 rd in receiving more favorites per tweet, 4 th in receiving more retweets per tweet, 5 th in posting a higher percentage of civil unrest related tweets, and 30 th in posting a higher percentage of community engagement and outreach tweets before vs. after the killing. The mean equaled 9.4 ((5+3+4+5+30)/5) across the five rankings and placed the Charlotte-Mecklenburg Police Department 1 st in the overall rank. It is worth noting that none of the police departments ranked (very) high on all five dimensions. In particular, if they increased their posting of civil unrest related tweets in the post-killing period, they were likely to reduce posting community engagement and outreach tweets.

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The current study explored police tweeting practices in a sample of 115 large agencies in the U.S., approximately two months before and after the killing of George Floyd that sparked the nationwide protests directed at the police in 2020.

In line with image repair theory, our analyses provided insights into the specific activities police agencies engaged in on social media in response to image damage and public reactions to those activities. Specifically, law enforcement agencies tweeted more frequently in the immediate aftermath of the killing and posted an increased number of civil-unrest related tweets. Police also continued to communicate case updates, perhaps directing public attention to their traditional role and responsibilities in fighting crime and maintaining order. On the other end, the public (at least those who were exposed to police departments tweets) showed a greater interest in engaging with law enforcement agencies. The rate at which the public favorited or retweeted a police tweet went up significantly following the George Floyd incident and stayed higher than before throughout the rest of the study period. Changes in the focal issues of police tweets (and potentially an increased attention to police behavior) may partially explain the increases in favorites and retweets received per tweet despite the police being in a legitimacy crisis. In particular, police tweets related to civil unrest, on average, received public reactions between twice and 20 times more than those of other categories of tweets received. By channeling and amplifying public energy towards this issue, social media provides opportunities for law enforcement to respond, engage, and rectify any misinformation with high efficiencies.

It may not be surprising that agencies that had the largest increases in public reactions (i.e., average favorite and retweet counts) or protest-related posts were from cities that saw major protest and riot activities, which aligns with the image repair thesis. However, we cannot conclude whether these increases were results of police engagement efforts aiming to genuinely improve police-community relations or socialization/legitimation efforts of reputation management. For instance, category 1 (or civil unrest related) tweets covered such topics as operational responses to the protest, crime and violence committed during the riots, challenges to racial justice in policing, and injuries and hostilities to police. These subcategories tap genuine concerns about racial injustice in the U.S. but also governance of citizens. We aimed to further distinguish subcategories within a focal issue (e.g., our labeled data included such information). Yet, the very low frequency of some subcategories in the labeled data and the limits of our prediction models prohibited us from pursuing this route. Nonetheless, it is clear that individual police agencies varied vastly in their social media usage. Not every agency was actively using Twitter to reach and engage or govern people. Twenty-four of the initial 139 large police agencies identified did not have a regular presence on Twitter. The final sample of 115 large police agencies also demonstrated tremendous variability in how often they tweeted, the types of tweets they tended to post, and public reactions to their social media content both at the baseline level and during the protest. Examining only a handful of agencies or a particular dimension of social media usage seems unlikely to provide a complete picture of police behaviors and citizen interactions on Twitter.

We contributed to the literature of police use of social media by creating a single indicator that combined measures of changes in the quantity of tweets, composition of tweets, and public responses to those tweets. While prior studies on police use of social media have looked at the number and types of police posts and the diffusion of those posts individually, few engaged in efforts to show where law enforcement agencies are relative to each other with respect to different sub-metrics and the overall standing of Twitter use. We controlled for baseline social media activity levels by separating our sample into higher versus lower activity agencies, thus adjusting for potential influences of agency-level factors on social media usage and its changes (e.g., agency size and jurisdiction population). Our combined indicator may serve as a useful first step toward cultivating responsible and effective use of social media by police. That said, the current study represents a preliminary effort at quantifying and understanding police social media usage in the context of the George Floyd protests and does not represent a comprehensive measurement of police performance on social media overall.

Given the great variability in police social media usage observed in our study and different possible interpretations of these efforts (e.g., engagement vs. socialization/legitimation), we do not recommend the deactivation of all police Twitter accounts as suggested by some [ 13 ]. Instead, we suggest a few avenues for future research (and practices) on responsible and effective use of social media by police, while pointing out the challenges associated with such inquiries.

First, future studies should explore why (and how) changes in police social media usage occur before and after a major social event. A few important challenges remain. We are uncertain of who are interacting with police on social media, which has important implications to its impact on police legitimacy or police-community relations. Much of the legitimacy crisis reflects ongoing frictions between police and disadvantaged/minority communities, the dynamic of which may not be captured by examining the overall responses received by police tweets. For instance, rather than reflecting improvements in community engagement activities or citizen trust, the increases in favorites and retweets of police-generated content might reflect more active reactions from a pre-existing pro-police audience. Police engagement efforts, however, are most needed towards minority and disadvantaged groups who are regularly contacted by law enforcement agencies. Whether and through what strategies police social media usage can target, reach, and respond to those groups would largely determine the efficacy of online police-community interactions, especially in repairing harm and (re)gaining trust. Otherwise, police communications on Twitter may not be fundamentally different from traditional means of communication and mainly fulfill a function of socialization/legitimation or appeal to those who already endorse police value and activities.

In addition, it is necessary to further investigate the detailed content generated by police on social media. While categorization, as in our case, is helpful in understanding shifts in general directions of police social media usage, topic modeling in natural language processing may uncover themes from a large corpus of tweets and assign individual tweets to different themes, better illustrating police motives for social media usage [ 42 , 43 ]. Adopting computer-assisted techniques to analyze (at a large scale) hyperlinks, images, and videos contained in police tweets should further improve our understanding of police social media usage [ 44 ]. Moreover, it would be helpful to investigate what organizational characteristics are associated with agency-level police motives for social media usage and adjustments after a major challenge.

Second, future studies should assess the impact of police social media usage on other performance measures, including public receptivity, police legitimacy and trust, crime investigation and clearance rate, community informal social control, among others. Such undertaking is challenging given the nature of these inquiries and the data needed for answering these questions yet important. Citizens’ experiences with the police affect their overall assessment of the police, but the vast majority of the American public do not have face-to-face contact with a police officer in any given year [ 45 , 46 ]. The extension from physical interaction with the police to social media platforms is worth further investigation.

Of note, although some consider liking and reposting behaviors less engaging or dialogical than “real” engagement activities such as community meetings, police-community collaborations, and joint problem-solving efforts, metric-driven engagement has an important meaning in and of itself in an algorithmic environment of social media in which information is curated and disseminated based on their relative popularity. Recognizing the limitations (e.g., ambiguous motives of police social media usage and messages not necessarily reaching targeted groups), scholars have argued that these metrics should be used to guide the development of social media strategies of law enforcement agencies [ 47 ], similar to how favorites and retweets are commonly used as indicators of success of a marketing strategy in the private industry. That said, agencies should be cautious not to seek reactions by posting content simply to appeal to their audiences. Authenticity and communicating negative but honest messages have been found to be key to maintaining police credibility on social media [ 15 ]. This helps explain the findings from our sentiment analysis. Police-generated social media content exuded greater negative than positive emotions following the George Floyd incident, but public reactions (i.e., average favorite and retweet counts per tweet) also went up tremendously during this time.

The study has limitations. First, police agencies may use social media platforms other than Twitter (e.g., Facebook or Nextdoor) to reach and engage (or govern) people during the same study period. Second, we did not explicitly investigate two-way police-citizen interactions on Twitter. Official police agency Twitter accounts often replied to other non-public Twitter accounts (e.g., a police chief’s account or police precinct account). Given the scale of the current study, manually checking each replying tweet was not feasible. Thus, we could not accurately assess the proportion of two-way police-citizen interactions on Twitter. Our preliminary check (excluding self-replying tweets) indicated that approximately 13% of all included 38,701 tweets were replies and that there were great variabilities in the proportion (e.g., over half of the Denver Police Departments tweets during the study period were replies, whereas several police agencies did not post any replying tweets during the same period of time) and the way official police agency Twitter accounts posted replying tweets. Additionally, we only analyzed the text content of police tweets, yet image or video content (also URLs) may meaningfully affect public reactions to police tweets. Moreover, retweeting does not necessarily reflect agreement with original content (e.g., retweets with users’ own negative reactions). In this sense, our findings show increased public participation in dialogues on public safety and social justice issues, not necessarily increased support for police-generated content online. Third, our classification algorithm was not perfect, but its accuracy was acceptable for our purpose. Fourth, the study examined police departments tweets approximately two months before and after the killing. Adjustments of Twitter usage made by police agencies may take longer to carry out. The scale and intensity of protests (and disruptions) at different jurisdictions may also affect how local police agencies adjust their social media presence, which we could not explicitly study. Future research should also explore geographic and political influences on police use of social media. Finally, given our focus on large police departments in the U.S., the results may not be generalizable to smaller agencies or agencies in other countries in their use of social media during a social crisis event.

The utility of social media in policing and public governance remains an understudied area, where case studies and qualitative evidence predominate. Through examining Twitter usage by 115 large U.S. police agencies following a major legitimacy crisis, we conclude that police reacted to the George Floyd incident on social media and that the public paid attention to and seemingly held positive attitudes toward those changes. Police agencies in our sample tweeted more frequently following the killing of George Floyd and posted more tweets related to civil unrest as well as case updates. These tweets received greater public reaction (through favorites and retweets), which persisted throughout the study period.

Nonetheless, a great variability emerged across agencies in their responses on social media (e.g., different rates and focuses of use), and the motives for the observed changes pre- and post-event were inconclusive. Future efforts are called for to address the limitations and ambiguities uncovered by this study about police use of social media (e.g., characteristics of those who interact with police on social media, communications that go beyond favorites and retweets, and police behaviors on social media platforms other than Twitter), and to find ways for police to responsibly and effectively utilize various communication platforms in the era of “big data”. For instance, a guideline or protocol of best practices for police social media usage may be developed and made public for comments prior to its approval and implementation, through which “selective transparency” may be curbed.

Supporting information

S1 table. a complete list of the 115 law enforcement agencies included in the study..

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S2 Table. Detailed categorization scheme used in the study.

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S3 Table. Random forest and multiclass boosted trees classifier.

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S4 Table. Exemplary tweets illustrating sentence-level pleasant or attractive vs. unpleasant or aversive emotion.

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S5 Table. Supplementary details about the results of the multiclass random forest classifier.

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Acknowledgments

The authors would like to thank Cynthia Lum, Laurie Robinson, James Willis, Charlotte Gill, and David Weisburd for their helpful comments on the earlier draft of the manuscript. The opinions expressed in this article are those of the authors and do not reflect the positions of any of the organizations with which the authors are affiliated.

• View Article
• PubMed/NCBI
• Google Scholar
• 2. National Academies of Sciences, Engineering, and Medicine. Proactive policing: effects on crime and communities. National Academies Press; 2018.
• 5. Crime Data Explorer. Federal Bureau of Investigation. https://crime-data-explorer.app.cloud.gov/pages/explorer/crime/crime-trend . Trend of homicide from 2010 to 2020. Accessed October 23, 2021.
• 6. Hu X, Lovrich NP. Electronic community-oriented policing: theories, contemporary efforts, and future directions. Lexington Books; 2020.
• 12. International Association of Chiefs of Police (IACP). Social Media. https://www.theiacp.org/sites/default/files/2019-05/Social%20Media%20Paper%20-%202019.pdf Accessed March 6, 2021.
• 17. Kim K, Oglesby-Neal A, Mohr E. 2016 Law enforcement use of social media survey. International Association of Chiefs of Police & the Urban Institute. 2017.
• 19. Lum C, Maupin C, Stoltz M. The impact of COVID-19 on law enforcement agencies (Wave 2). International Association of Chiefs of Police & the Center for Evidence-Based Crime Policy, George Mason University. Washington, DC. 2020. https://www.theiacp.org/sites/default/files/IACP_Covid_Impact_Wave2.pdf . Accessed December 6, 2021.
• 27. Denef S, Bayerl PS, Kaptein NA. Social media and the police: tweeting practices of British police forces during the August 2011 riots. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems; 2013.
• 36. Bureau of Justice Statistics, U.S. Department of Justice. Law Enforcement Management and Administrative Statistics (LEMAS), 2016. https://bjs.ojp.gov/data-collection/law-enforcement-management-and-administrative-statistics-lemas . Accessed October 2, 2021.
• 37. Kearney MW, Heiss, A, Briatte F. Package ‘rtweet’. https://cran.r-project.org/web/packages/rtweet/rtweet.pdf . Accessed October 23, 2021.
• 38. Wojcik S, Hughes A. Sizing up Twitter users. Pew Research Center; 2019.
• 40. Liu B. Sentiment Analysis: mining sentiments, opinions, and emotions (2nd edition); Cambridge University Press; 2020.
• 41. Rinker T. Package `sentimentr’. https://cran.r-project.org/web/packages/sentimentr/sentimentr.pdf . Accessed October 23, 2021.
• 42. Yan X, Guo J, Lan Y, Cheng X. A biterm topic model for short texts. Proceedings of the 22nd International Conference on World Wide Web; 2013.
• 45. Gallagher C, Maguire ER, Mastrofski SD, Reisig MD. The public image of police: final report to the IACP by the George Mason University Administration of Justice Program. International Association of Chiefs of Police; 2001.
• 46. Harrell E, Davis E. Contacts between police and the public, 2018–statistical tables. Bureau of Justice Statics Report, NCJ. 2020;255730.

Violence Trending: How Socially Transmitted Content of Police Misconduct Impacts Reactions toward Police Among American Youth

The Emerald International Handbook of Technology-Facilitated Violence and Abuse

ISBN : 978-1-83982-849-2 , eISBN : 978-1-83982-848-5

Publication date: 4 June 2021

Videos of police abuse are often spread through technology, raising questions around how perceptions of police are impacted by these images, especially for 18–24-year-olds who are constantly “logged on.” Limited research investigates the impact of social media on attitudes toward police accounting for age and race. The present study utilizes 19 in-depth interviews with a diverse sample of urban college students who regularly use social media in order to understand how they have been impacted by this content. The findings suggest the necessity of using an intersectional framework to understand the impact of tech-witnessed violence. While no gender differences were uncovered, racial differences did surface. White participants described being minimally influenced by videos of police misconduct, rationalizing it as a “few bad apples.” In contrast, participants of color, except those with family members in law enforcement, described being negatively impacted. Viral content contributed to negative opinions of police, emotional distress, and fears of victimization. Ultimately, videos of police brutality do not impact young populations equally. Instead, they are comparatively more harmful to young people of color who spend more time on social media, can envision themselves as the victims, and experience feelings of fear, despair, and anger after watching these videos.

• Police misconduct
• Social media and race
• Digital violence
• Perceptions of law enforcement
• Abhorrent violent behavior

Novich, M. and Zduniak, A. (2021), "Violence Trending: How Socially Transmitted Content of Police Misconduct Impacts Reactions toward Police Among American Youth", Bailey, J. , Flynn, A. and Henry, N. (Ed.) The Emerald International Handbook of Technology-Facilitated Violence and Abuse ( Emerald Studies In Digital Crime, Technology and Social Harms ), Emerald Publishing Limited, Leeds, pp. 271-288. https://doi.org/10.1108/978-1-83982-848-520211020

Emerald Publishing Limited

Copyright © 2021 Madeleine Novich and Alyssa Zduniak. Published by Emerald Publishing Limited. This chapter is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of these chapters (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode.

This chapter is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of these chapters (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode .

Introduction

Attitudes and reactions toward police are complex and result from various factors including gender ( Brown & Benedict, 2002 ), race ( Brunson, 2007 ; Gau & Brunson, 2007 ), and age ( Brunson, 2007 ; Flexon, Lurigio, & Greenleaf, 2009 ). First-hand and vicarious encounters with police are also impactful in shaping attitudes ( Papachristos, Braga, & Hureau, 2012 ; Rosenbaum, Schuck, Costello, Hawkins, & Ring, 2005 ; Tyler, 2006 ; Weitzer, 2002 ). Contemporary literature demonstrates that face-to-face encounters can have profound effects on an individual's opinion of law enforcement, especially if the interaction is marred by perceptions of biased, disrespectful, indifferent, and untrustworthy officers ( Novich & Hunt, 2016 ; see also Tyler, 2006 ).

Emerging evidence suggests that vicarious experiences shared by family and friends through social networks can also shape one's perspective of and response to police ( Dowler & Zawilski, 2007 ; Lim, 2015 ; Papachristos et al., 2012 ). There has been growing concern and awareness of police misconduct and brutality as a result of viral social media ( Tynes, Willis, Stewart, & Hamilton, 2019 ). Research demonstrates that media functions as a key mechanism for shaping attitudes toward police ( Dowler & Zawilski, 2007 ) and, perhaps more concerning, witnessing officer-initiated abhorrent violent behavior (AVB) causes psychological trauma, depression, and posttraumatic stress among viewers who can identify with the victim ( Tynes et al., 2019 ). Police misconduct shared through social media may be more harmful to young people of color when compared with their white counterparts because they invest more time and energy into social media, and social media increases their ability to witness misconduct against people of their racial and ethnic background. Conversely, social media provides young people of color a platform to express themselves and raise concerns relating to their marginalized social experience ( Grasmuck, Martin, & Zhoa, 2009 ; Lee, 2011 ). It is therefore important to investigate perceptions of and responses to police using an intersectional framework that accounts for race, age, and social media usage.

In response, this chapter is premised on a study that utilizes interviews with a racially diverse sample of college-aged participants and examines if and how their perceptions and feelings toward police are impacted by social media and videos of police violence transmitted via technology. The chapter will first provide an overview of current literature on attitudes toward police. The second section will describe the methodological strategies employed in the study, and the third section will present the findings. Finally, the chapter will end with a discussion of how the salient findings, which are that participants of color are disproportionately negatively impacted by violent police videos, fit into the broader context of contemporary empirical research.

Literature Review

Attitudes toward the police.

There are many factors that contribute to an individual's attitude toward police. Extensive research indicates that race and ethnicity are a significant predictor in determining attitudes toward police ( Brown & Benedict, 2002 ; Brunson, 2007 ; Gau & Brunson, 2007 ; Novich & Hunt, 2016 ). In America, people of color, especially young Black and Latino men, have more negative views of the police when compared with white men ( Brown & Benedict, 2002 ; Cheurprakobkit, 2000 ; Weitzer & Tuch, 1999 ). This is likely due to minority populations experiencing greater levels of poor officer treatment, including discriminatory and aggressive police behavior ( Brown & Benedict, 2002 ; Fratello, Rengifo, & Trone, 2013 ; Novich & Hunt, 2016 ; Weitzer & Tuch, 1999 ).

Attitudes toward police also appear to be influenced by gender, whereby females tend to hold more favorable opinions of police when compared with male counterparts ( Weitzer & Tuch, 1999 ). However, American women of color generally view police more negatively when compared with white women ( Brick, Taylor, & Esbensen, 2009 ; Hurst, McDermott, & Thomas, 2005 ). Age is also significant, with young people more likely to view police less favorably than older people ( Cheurprakobkit, 2000 ; Hurst, Frank, & Browning, 2000a ). This may be due to the increased probability of a young person being stopped by the police than an older one or the tendency of older residents to desire safety in their community, which law enforcement can provide ( Brown & Benedict, 2002 ; Lee, Lim, & Lee, 2015 ; Lim, 2015 ).

Overall, young populations hold strong opinions about police ( Brick et al., 2009 ; Brunson, 2007 ; Flexon et al., 2009 ; Leiber, Nalla, & Farnworth, 1998 ) and these attitudes are profoundly impacted by direct experiences with law enforcement ( Brick et al., 2009 ; Flexon et al., 2009 ; Leiber et al., 1998 ; Novich & Hunt, 2016 ; Rosenbaum et al., 2005 ). Encounters where individuals perceive police as dishonest or untrustworthy, or feel stripped of their agency, negatively impact perceptions of police legitimacy (see Tyler, 2006 ). However, personal relationships can mitigate negative responses, especially for individuals that have a personal connection to a law enforcement officer ( Lee et al., 2015 ; Lim, 2015 ).

Impact of Social Media on Perceptions of Police

Emerging evidence suggests that attitudes toward law enforcement are also formed via vicarious experiences from family, friends, and community members ( Brunson, 2007 ; Hurst, Frank, & Browning, 2000b ; Papachristos et al., 2012 ; Rosenbaum et al., 2005 ; Weitzer, 2002 ; Wu, 2013 ). Most citizens in the population have an opinion on law enforcement, despite the fact that “[four] out of [five] Americans do not have direct contact with police officers during any given year” ( Rosenbaum et al., 2005 , p. 360). Opinions about police are likely formed as a result of experiences witnessed or learned about from family, friends, or posts on their social networks ( Papachristos et al., 2012 ). There are several theoretical frameworks that may explain the impact of socially transmitted videos of police behavior on perceptions of law enforcement. Research suggests that media is “decoded” or understood differently depending on the unique background of each viewer (see Hall, 1980 , p. 107). The different groups of viewers, of which there are many, may understand media differently depending on an individual's self, gender, family, class, nation, race/ethnicity, sexual orientation, and age ( Fiske, 1986 ; Hall, 1980 ).

In terms of age, social networking platforms may create a social modeling atmosphere for young people. These platforms are where young people learn through observing others, especially those they hold in esteem, and follow suit (see Lim, 2015 ). Premised on Bandura's (1962) imitation theory, research suggests that there are three kinds of social modeling: live (an individual demonstrating a certain behavior in real time); verbal (descriptions or explanations of a particular behavior); and symbolic (real or fictional characters found in media, books, or online). “Symbolic” personas, both real and fake, offer a behavioral model through secondary sources like social media, television, and literature ( Lim, 2015 , p. 675). Social media sites like Facebook and Instagram create easy access to symbolic models since friends, family, and groups can post videos and caption them so that the “correct” opinion can be easily obtained while scrolling through a feed. Due to their more persistent uses of these sites, young people may be more impacted by highly publicized events. With regards to police specifically, research suggests that young people's reactions may be significantly impacted if those highlighted virtual events focus on procedural injustice, police misconduct, and AVB on behalf of police ( Reisig & Correia, 1997 ; Tynes et al., 2019 ; Weitzer, 2002 ).

Indeed, people are negatively impacted by witnessing AVB and/or traumatic events online (TEO) ( Feinstein, Audet, & Waknine, 2014 ; Holman, Garfin, & Silver, 2013 ; Tynes et al., 2019 ). Seeing graphic footage of extreme violence can evoke involuntary memories ( Clark, Holmes, Woolrich, & Mackay, 2016 ) or can cause acute stress, posttraumatic stress disorder (PTSD), and depression, especially if such footage is viewed frequently ( Feinstein et al., 2014 ; Holman et al., 2013 ). While people of all backgrounds are no doubt harmed, witnessing socially transmitted AVB perpetrated by police may be more harmful for populations of color. Not only does the footage contribute to negative attitudes toward law enforcement ( Weitzer, 2002 ), but also it may cause individual and community-spread psychological trauma ( Tynes et al., 2019 ).

Social media posts that showcase police in a negative light affirm what minority communities have experienced for decades ( Aymer, 2016 ; Bonilla & Rosa, 2015 ; Bryant-Davis, Adams, Alejandre, & Gray, 2017 ). Children of traditionally marginalized ethnicities are raised to fear and expect police harassment, and this fear limits their mobility and informs social behavior ( Bryant-Davis et al., 2017 ). Social media featuring police misconduct solidifies these feelings of “fear, despair, and anxiety,” which has a traumatic impact on the brain and can lead to brain dysregulation, stress, PTSD, and self-destructive behavior ( Bryant-Davis et al., 2017 , p. 855). Further, this type of content raises fears of victimization among social media consumers of color ( Callanan, 2012 ; Dowler, 2003 ; Kohm, Waid-Lindberg, Weinrath, Shelley, & Dobbs, 2012 ). Higher levels of fear are found in the African American community and are generated when the violence portrayed through the media source is in the same geographical area as the individual viewing the content ( Callanan, 2012 ; Dowler, 2003 ; Kohm et al., 2012 ). Additionally, Tynes et al. (2019) examined the impact of witnessing viral videos of race-related police killings of unarmed citizens among youth of color and found that viewing AVB that was directed at one's own racial/ethnic group was related to an increase in PTSD and depression. The researchers also raised concerns that, given how easily transmitted this content is among peers, the negative impact may contribute to community-wide mental health problems.

Racial differences may be further exacerbated if the individuals are “logged on” often. Contemporary research suggests that people of color are heavy consumers of media content of police misconduct and are more likely to believe it is frequently occurring ( Dowler & Zawilski, 2007 ; Tynes et al., 2019 ). Additionally, research suggests that people of color interact with social media differently than their white counterparts ( Chan, 2017 ; Grasmuck et al., 2009 ; Lee, 2011 ). People of color invest more time and energy into networking platforms because of the opportunity it creates to be heard and to connect with others of similar racial backgrounds. On social media, users can consume information through posts, determine its relevance to their own experience, and further develop their understanding of their racial identity ( Chan, 2017 ; Grasmuck et al., 2009 ).

How responses toward police are formed is complex and requires an intersectional framework. Age and race can play an important role, as does first-hand and vicarious encounters with law enforcement. Social media and the transmission of police violence through social networks is increasingly of interest to researchers, especially when examining young people of color. In response, this study utilizes interviews with young, heavy social media users to investigate how technologically transmitted videos of police misconduct may impact their reactions toward officers. Paying close attention to racial differences, this investigation attempts to narrow the scholarly understanding of how social media may influence their feelings about police.

Methodology

The qualitative data were collected from September to November 2018 on an urban college campus as part of a semester-long undergraduate Research Methods course. These interviews solicited feedback on participants' experience with and attitudes toward police, social media usage, and the impact of video content on opinions of law enforcement. The data included 19 participants: men (53%, n = 10) and women (47%, n = 9). The largest ethnic group was Latinx (42%, n = 8), followed by white (37%, n = 7), Asian (11%, n = 2), and African Americans (11%, n = 2). The target age range was 18–24 years, given that this age group consumes social media at higher rates and visit more platforms than other age groups (see Smith & Anderson, 2018 ). The participants indicated that they used one or more popular social media sites including Facebook, Twitter, and YouTube.

The interviews were conducted in English, typically lasted 30 minutes, and took place in various campus locations. No compensation was provided. The data were digitally recorded, transcribed verbatim, redacted, and anonymized. The interviews were semistructured and included open-ended questions concerning the participants' opinion of police, experiences with content about police shared on social media, and if and how they believed social media impacted their perceptions of police. Each interview was read repeatedly and was systematically inductively coded. The analysis was refined using narrative analysis, where long narratives of personal experiences were organized sequentially and broken down into coded categories salient to the current investigation ( Presser & Sandberg, 2015 ), as well as progressive focusing, which was the ongoing evaluation of relationships between themes, trends, and concepts throughout the entire coding and analysis process ( Chambliss & Schutt, 2016 ). The data were arranged on matrices to ensure that patterns, comparisons, and deviant cases could be assessed thoroughly ( Maxwell, 1996 ) and all cases were included ( Silverman, 2006 ).

There were several limitations. The interviews were conducted by different individuals so the follow-up questions were not standardized. The research used a college-aged population, which is often viewed as a convenience sample, not representative of the larger society, and can produce findings that may not be generalizable. However, this population was the intended target because this age group is most active on social media compared with other age groups ( Arceneaux & Dinu, 2018 ; Chan, 2017 ; Lee, 2011 ; see also Smith & Anderson, 2018 ). Also, the sample size may be considered small, raising concerns of generalizability. However, the smaller sample size allowed for a more nuanced inquiry which can enhance the validity of in-depth investigations ( Crouch & McKenzie, 2006 ). Finally, the research is based on US-centric data where police and populations of color, of whom are ethnic minorities, have a unique history of tension and violence. As such, the findings may not be applicable to other nations that do not share similar historical challenges. Despite these limitations, the impact of abhorrent violent police behavior was discussed repeatedly by participants, often without prompting, providing a rich qualitative data source for this investigation.

Attitudes toward the Police: The Racial Divide

Opinions about police are complicated and formed as a result of many factors (see Brown & Benedict, 2002 ). As one Latina aptly noted, “I would say [my attitude toward police] is a sum of a lot of things.” Attitudes toward police can be shaped by face-to-face interactions ( Tyler, 2002 ), television and fictional media ( Donovan & Klahm, 2015 ), opinions from family and friends, and vicarious experiences of police behavior, including stories shared between friends and family and videos of police transmitted through news and social media ( Brown & Benedict, 2002 ; Reisig & Correia, 1997 ; Weitzer & Tuch, 1999 ). However, the relative influence of each factor is not wholly understood and may impact individuals differently. This may be especially so with regard to people of different racial and ethnic backgrounds.

I'm not the biggest fan of the police...they let their power get to their head...when they put that uniform on, they are a different person. I feel like it gives them too much power and authority…it gives them the right to disrespect us…. I've had times where I would hop the train and one of ‘em handcuffed me so bad I had a mark on my wrist all day.

For three participants, negative opinions about law enforcement stemmed from the belief that the police were “racist.” A Black female, for instance, described the police as “prejudiced,” basing her opinion on racially motivated incidents she witnessed. While her attitude toward police was premised on vicarious experiences, two participants indicated their opinion was shaped by first-hand encounters with police. One Latino male, for example, lamented that he “never had a positive experience” with police and described feeling “uncomfortable” around law enforcement, especially “white officers.”

While these narratives reflect the majority of the participants of color, three participants of color expressed positive opinions about the police. One explained he was former military and had a positive encounter with the military police. Two others indicated that they had family members who were in law enforcement. One Latina woman succinctly explained, “I come from a family of … cops so I like them.” Despite these outliers, the findings reflect extensive research that populations of color have negative attitudes toward police, especially when compared with their white counterparts.

Consistent with previous research, the white participants had generally more favorable attitudes toward the police. Overall, four of the seven 1 white participants described law enforcement favorably, indicating they trusted them, “appreciate what they do,” and generally felt they were “good” people who did their job well. One white female stated, “I like the police… I trust them to do their job and to protect the citizens of this country. To be unbiased members of the community.” Similarly, a white male noted, “I believe most police officers are good and do their job the way they should.” Like the two participants of color with relatives in law enforcement, one white female explained that she had family members that were officers and expressed that she had “a strong personal connection to law enforcement.”

There were two outliers who expressed negative attitudes toward the police. These cases appeared to have serious extenuating circumstances of experiencing or witnessing extreme violence. One white female, for example, indicated she had multiple negative encounters including one where she was sexually assaulted by an officer. Aside from these two, the attitudes toward the police were clearly delineated along racial lines where white participants’ perceptions were more favorable than the participants of color.

The Impact of Videos Seen on Social Media

Social media for many is a source of news and a means to transmit popular culture, social justice content, and information on trending topics between friends, family, and trusted networks. This includes viral videos of police misconduct. Indeed, every participant confirmed they used social media (19 of 19), and most (18 of 19) reported seeing videos of police through their various social networks. This included positive videos, where police were described as doing something kind or helpful, and negative videos, where police were described as doing something harmful against civilians. The slight majority ( n = 11 2 of 19) of participants described only having seen negative videos of police. The remaining participants (7 of 19) described viewing both types of videos.

Limited Impact: Videos Focus on “Bad Apples”

You can [see videos of] police officers giving CPR to little kids, to a police officer shooting a guy who turns out to be unarmed. Anytime somebody loses their life regardless of what the reason is, it's always unfortunate because that's someone son or daughter…[but] I try not to be too reactionary because one video can't change your whole mindset, it's sort of like the “bad apple” analogy.

These narratives indicate that videos shared on social media, even ones of intense violence, may not shift an individual's orientation toward police.

I never thought about the possibility of there being a bad police officer until I saw it on social media, but I know that they are not all like that... [Social media] reaffirmed what I already knew. But after seeing all those brutal videos…I know there are “bad apples.”

These findings suggest that social media may not have the ability to change opinions among some populations, including white individuals who are supportive of law enforcement. Given this is in opposition to what was the participants of color reported, this finding indicates that the impact of social media may be less impactful and less harmful for white youth when compared with young people of color.

Videos Can Shape Opinions: “Videos Impacted the Way I Think About Police”

For 8 of the 19 participants, videos of violent police behavior were described as contributing to their opinions of police and causing feelings of fear and distress. Among these eight, seven held unfavorable attitudes about police and all were participants of color. While not described as being the sole determinant for their attitudes, social media, and specifically videos of police violence, was explicitly mentioned as a contributing factor in how their perspectives and reactions toward police were formed.

There was a video of a man that got shot at a gas station…he wasn't doing anything, he was just getting gas, when this cop came over, and…the guy in the driver's seat went into the glove department to get his driver's license, [and] when he reached down, the cop just shot him. [The officer] said that he thought [the victim] was getting a gun…even though he had asked him for the insurance stuff. It seemed senseless, and like he had no reason to even touch his gun. The guy had his hands up, it wasn't like he was rushing to get into the glove compartment. That just seemed completely harmless and straight up murder…. It's a system that's corrupt.

I saw this video of these girls from Texas…they went to some pool party…it got shut down…and one of the cops put every single [youth of color] on the ground and he was on top of some girl and she was Black. For like five minutes with his knee on her neck and she wasn't even doing anything. She was just trying to have a conversation and ask him why he was doing what he was doing and he was going crazy on her…. I draw a difference between White police officers and minority police officers…. I just don't trust [White officers].

We watched this video…. It was like a pool party and Black people were invited to [the] party…. Someone called the cops [and] basically the cops came and made the Black people leave. This cop who was White, he was like middle aged, he was sitting on a young girl in her bikini restraining her. She was like half naked and scared. I started tearing up because she wasn't doing anything, she was just asking him to get off and he was just on her.

There was this one video where there was this White cop basically sitting on top of this Black guy…. [The officer] thought the Black guy was gonna take something out his pockets and [the officer] just started shooting him point blank in the chest. It's the most gruesome thing I've seen really. It's sick to me and I hate even thinking about it…. I see things on social media everyday really that's related to police and most of it is in a negative way.... These videos are important. We see ‘em every day and they kind of shape our thinking.

I think [news of police misconduct] does impact me when it is relative to my location. Like when I see stories or videos of cop interactions in [home state] or New York…. It is scary to me because it could potentially happen to me. There was this police officer in New York last year that was going around and raping women.... This was really frightening to me because he was targeting women of color.

The police accused Eric Garner of selling cigarettes…he said he was not, and the police continued to arrest him anyway, even putting him in a chokehold, and he was not struggling or resisting at all until the police did that, and Eric Garner even said to the police that he couldn't breathe while he was being held in a chokehold but the police still continued…. He started coughing and suffocating because of that.

[The] Eric Garner video... made me...feel unsafe. Not me specifically, but for my male relatives... God forbid my Dad or Grandpa goes outside of [urban hometown]. I would fear for their safety more than if they were [in urban hometown].

It was a video on Sandra Bland [that had the biggest impression on me] and how she was a black teacher that got pulled over by a police officer and it got a little out of hand and she got arrested. While in jail for three days, she was found dead and it was so-called suicide…. This video made me feel fearful because it was someone of my own race that it happened to and with past history, people from my racial background don't have the best relationships with authorities.

These findings suggest that videos can not only impact perceptions of police but also cause negative emotional, physical, and mental reactions from viewers. Videos of police misconduct may be especially important among populations of color who may become fearful of being personally subjected to racially motivated police violence.

I always had that positive image [of] and encounters with police officers, but knowing how history goes and what has been happening lately in the news, my opinion of the police has begun to lean more toward a negative light…. The more negative encounters, like the ones I've seen on social media and the news have more of an impact on me and my opinion.

For others, although videos were important, the relative impact was described as less impactful than face-to-face encounters. Several participants (5 of the 19) directly indicated that their in-person interactions with police were more meaningful in shaping their opinions than what they witnessed on social media. This was especially so if the face-to-face encounters were negative, as was the case with four of the five participants. One Latino male stated, “We are always on social media so that's maybe where I get my feelings but most of it comes from my face-to-face encounters.” This sentiment was echoed by several others as well, including another Latino male who stated, “I feel that my personal experiences are stronger influences, but social media does give you more information and brings awareness to issues around the world.” Despite this, however, these findings suggest that videos of police behavior can shape opinions about law enforcement, although the relative impact may range from profoundly influential to somewhat influential. Further, the videos may be especially meaningful for individuals of color because they can raise concerns of police brutality, abuse of authority, racism, distrust, trauma, and fear of victimization.

Reactions toward police derive from a complex mixture of identity, experience, and socialization. Consistent with extensive literature, the research conducted in this study shows that the influence of parents, friends, face-to-face encounters, vicarious experiences, and social media contributes to the development of young people's perspectives of law enforcement (see Brown & Benedict, 2002 ). In line with previous American studies, evidence shows that perspectives of police differ among racial and ethnic identities. The participants of color in this study, except those who had family in law enforcement, generally held negative views of police ( Brunson, 2007 ; Gau & Brunson, 2007 ). These participants described disliking the police due to perceptions of them being racist, untrustworthy, and abusing their power ( Fratello et al., 2013 ). On the contrary, white participants, except for the two that had particularly egregious face-to-face encounters, expressed more favorable opinions of law enforcement ( Brown & Benedict, 2002 ). The white participants were generally appreciative of police officers' work and perceived them as good, hard working people. This research shows that race and ethnicity can impact perceptions of law enforcement ( Brunson, 2007 ; Fiske, 1986 ; Gau & Brunson, 2007 ; Novich & Hunt, 2016 ), with Black participants more likely to have the most negative views, their white counterparts the most positive, and other ethnic identities falling in the middle ( Brown & Benedict, 2002 ; Cheurprakobkit, 2000 ; Rosenbaum et al., 2005 ). While these findings support previous work, the examination of social media offers innovative evidence on how different populations synthesize police content shared through their social networks.

Although the research yielded limited gender discrepancies, possibly due to sample limitations, clear racial differences surfaced. Participants of all ethnoracial identities in the study referred to viral videos that they remembered seeing, indicating the ability of this content to reach different populations. However, a majority of the white participants indicated that social media had a limited impact on their perceptions of police and tended to rationalize videos of police misconduct by isolating these incidents to a few “bad apples” that do not represent the whole. Many white participants appeared to use positive social media to validate preexisting positive opinions, while dismissing negative content as biased or out of context. The content shared on social media did not seem to have a significant impact on the formation of white participants' attitudes toward police.

This was a stark contrast to the participants of color ( Weitzer, 2002 ) who “decoded” trending police violence differently than their white counterparts ( Fiske, 1986 ; Hall, 1980 ). The witnessing of AVB and/or TEO directly contributed to negative attitudes toward police and raised concerns of abuse of authority, distrust, and excessive use of power. These data suggest that negative videos can have detrimental consequences on perceived police legitimacy ( Novich & Hunt, 2016 ; Tyler, 2006 ). This was the case even among those who had positive face-to-face encounters with police. This is significant because previous research has suggested that face-to-face encounters are most important when forming opinions of police (see Tyler, 2006 ). The research suggests that this may not always be the case among young people of color.

Moreover, the witnessing of AVB and TEO had serious negative consequences for participants of color. The findings suggest that the AVB and TEO may be a form of tech-facilitated abuse due to the emotional manipulation of viewers. Not only did several study participants easily recall memories of AVB and TEO, which is linked to acute stress ( Clark et al., 2016 ), but also AVB and TEO engendered extreme distress (i.e., the viewer started crying), feelings of nauseated disgust, and anxiety – reactions associated with poor mental health ( Feinstein et al., 2014 ; Holman et al., 2013 ). Further, the racially motivated police violence witnessed by participants was applied to real-world expectations whereby they personally identified with the victims and raised concerns of fear of victimization for themselves, family members, and/or friends (see Tynes et al., 2019 ). This contributed to heightened levels of stress and trauma (see Bryant-Davis et al., 2017 ; Tynes et al., 2019 ). These reactions may be further exacerbated given the “daily” frequency in which participants reported seeing AVB and TEO in their feeds (see Feinstein et al., 2014 ; Holman et al., 2013 ). Of additional concern is the widespread community consequences ( Tynes et al., 2019 ). Given how readily shared AVB is among family and friends, which may be rationalized as a way of inspiring social awareness and a desire for justice, whenever it is forwarded the harm spreads and makes each person unknowingly complicit in disseminating technology-facilitated abuse.

The evidence in the present study indicates young people of color interpret shared content differently than their white counterparts. Young people of color are not only more sensitive to the material ( Lim, 2015 ) but also raise more concerns of police legitimacy ( Novich & Hunt, 2016 ) and experience greater levels of trauma, fear, concerns of victimization, and anger ( Bryant-Davis et al., 2017 ; Tynes et al., 2019 ). As such, this study highlights the need for police departments, especially those working with diverse populations, to implement workshops like procedural justice training which focus on establishing respect through courteous interpersonal treatment ( Tyler, 2006 ). These practices may help reduce violent police behavior while simultaneously improving perceptions of legitimacy and relationships with young communities of color ( Novich & Hunt, 2016 ).

Second, this research also demonstrates the need for police departments to take immediate action following the circulation of AVB videos in order to mitigate trauma, emotional distress, and concerns of victimization. This may come in the form of providing mental health support to the communities directly impacted and police leadership taking accountability for officer misconduct. This may be a critical way in which police can improve public support and acknowledge harm caused. Ultimately, this research has shown the disproportionate emotional and psychological impact of AVB showcasing police violence on young people of color. For a world constantly “logged on,” therein lies a responsibility to recognize social media's influence on police-community relationships and its ability to enable widespread technologically facilitated abuse. Recognizing this responsibility is especially necessary in order to understand those who are inordinately impacted by viral content and calls to attention the critical need to put practices into place that mitigate the subsequent harm.

One white male described himself as “neutral” regarding his opinion about police and was not placed in either the positive or negative category.

One student reported seeing a video where the police were being disrespected. This was considered a negative police video. The other 10 described negative videos as police misconduct.

Two students of color who held negative opinions about police also indicated that social media had a limited impact on their perceptions of police. For one, as will be further discussed in detail, face-to-face encounters were more impactful than social media.

One Latino male noted how his opinion of police changed to be less negative and more neutral as a result of witnessing videos of officers engaging in positive and helpful behavior.

Arceneaux and Dinu, 2018 Arceneaux , P. C. , & Dinu , L. F. ( 2018 ). The social mediated age of information: Twitter and Instagram as tools for information dissemination in higher education . New Media & Society , 20 ( 11 ), 4155 – 4176 . doi: 10.1177/1461444818768259

Aymer, 2016 Aymer , S. R. ( 2016 ). “I can't breathe”: A case study—helping black men cope with race-related trauma stemming from police killing and brutality . Journal of Human Behavior in the Social Environment , 26 ( 3–4 ), 367 – 376 . doi: 10.1080/10911359.2015.1132828

Bandura, 1962 Bandura , A. ( 1962 ). Social learning through imitation . In M. R. Jones (Ed.), Nebraska symposium on motivation (pp. 211 – 274 ). Lincoln, NE : University of Nebraska Press .

Bonilla and Rosa, 2015 Bonilla , Y. , & Rosa , J. ( 2015 ). #Ferguson: Digital protest, hashtag ethnography, and the racial politics of social media in the United States . American Ethnologist , 42 ( 1 ), 4 – 17 . doi: 10.1111/amet.12112

Brick et al., 2009 Brick , B. T. , Taylor , T. J. , & Esbensen , F. ( 2009 ). Juvenile attitudes toward the police: The importance of subcultural involvement and community ties . Journal of Criminal Justice , 37 ( 5 ), 488 – 495 . doi: 10.1016/j.jcrimjus.2009.07.009

Brown and Benedict, 2002 Brown , B. , & Benedict , W. R. ( 2002 ). Perceptions of the police . Policing: An International Journal of Police Strategies & Management , 25 ( 3 ), 543 – 580 . Retrieved from http://www.observatoriodeseguranca.org/files/p543.pdf

Brunson, 2007 Brunson , R. K. ( 2007 ). “Police don't like Black people”: African-American young mens' accumulated police experiences . Criminology & Public Policy , 6 ( 1 ), 71 – 101 . doi: 10.1111/j.1745-9133.2007.00423.x

Bryant-Davis et al., 2017 Bryant-Davis , T. , Adams , T. , Alejandre , A. , & Gray , A. A. ( 2017 ). The trauma lens of police violence against racial and ethnic minorities . Journal of Social Issues , 73 ( 4 ), 852 – 871 . doi: 10.1111/josi.12251

Callanan, 2012 Callanan , V. J. ( 2012 ). Media consumption, perceptions of crime risk and fear of crime: Examining race/ethnic differences . Sociological Perspectives , 55 ( 1 ), 93 – 115 . doi: 10.1525/sop.2012.55.1.93

Chambliss and Schutt, 2016 Chambliss , D. F. , & Schutt , R. K. ( 2016 ). Making sense of the social world: Methods of investigation . Thousand Oaks, CA : Sage Publications, Inc .

Chan, 2017 Chan , J. ( 2017 ). Racial identity in online spaces: Social media's impact on students of color . Journal of Student Affairs Research and Practice , 54 ( 2 ), 163174 . doi: 10.1080/19496591.2017.1284672

Cheurprakobkit, 2000 Cheurprakobkit , S. ( 2000 ). Police-citizen contact and police performance: Attitudinal differences between Hispanics and non-Hispanics . Journal of Criminal Justice , 28 ( 4 ), 325 – 336 . doi: 10.1016/S0047-2352(00)00042-8

Clark et al., 2016 Clark , I. A. , Holmes , E. A. , Woolrich , M. W. , & Mackay , C. E. ( 2016 ). Intrusive memories to traumatic footage: The neural basis of their encoding and involuntary recall . Psychological Medicine , 46 ( 3 ), 505 – 518 . doi: 10.1017/S0033291715002007

Crouch and McKenzie, 2006 Crouch , M. , & McKenzie , H. ( 2006 ). The logic of small samples in interview-based qualitative research . Social Science Information , 45 ( 4 ), 483 – 499 . doi: 10.1177/0539018406069584

Donovan and Klahm, 2015 Donovan , K. M. , & Klahm , C. F. ( 2015 ). The role of entertainment media in perceptions of police use of force . Criminal Justice and Behavior , 42 ( 12 ), 1261 – 1281 . doi: 10.1177/0093854815604180

Dowler, 2003 Dowler , K. ( 2003 ). Media consumption and public attitudes toward crime and justice: Relationship between fear of crime, punitive attitudes, and perceived police effectiveness . Journal of Criminal Justice and Popular Culture , 10 ( 2 ), 109 – 126 . Retrieved from https://www.researchgate.net/publication/285675137_Media_consumption_and_public_attitudes_toward_crime_and_justice_The_relationship_between_fear_of_crime_punitive_attitudes_and_perceived_police_effectiveness

Dowler and Zawilski, 2007 Dowler , K. , & Zawilski , V. ( 2007 ). Public perceptions of police misconduct and discrimination: Examining the impact of media consumption . Journal of Criminal Justice , 35 ( 2 ), 193 – 203 . doi: 10.1016/j.jcrimjus.2007.01.006

Feinstein et al., 2014 Feinstein , A. , Audet , B. , & Waknine , E. ( 2014 ). Witnessing images of extreme violence: A psychological study of journalists in the newsroom . JRSM Open , 5 ( 8 ), 1 – 7 .

Fiske, 1986 Fiske , J. ( 1986 ). Television: Polysemy and popularity . Critical Studies in Mass Communication , 3 , 391 – 408 . doi: 10.1080/15295038609366672

Flexon et al., 2009 Flexon , J. L. , Lurigio , A. J. , & Greenleaf , R. G. ( 2009 ). Exploring the dimensions of trust in the police among Chicago juveniles . Journal of Criminal Justice , 37 ( 2 ), 180 – 189 . doi: 10.1016/j.jcrimjus.2009.02.006

Fratello et al., 2013 Fratello , J. , Rengifo , A. , & Trone , J. ( 2013 ). Coming of age with stop and frisk: Experiences, self-perceptions, and public safety implications: Summary Report . New York, NY: Vera Institute of Justice . Retrieved from http://www.vera.org/stop-and-frisk-summary-report

Gau and Brunson, 2007 Gau , J. , & Brunson , R. ( 2007 ). Procedural injustice, lost legitimacy, and self-help: Young males' adaptations to perceived unfairness in urban policing tactics . Journal of Contemporary Criminal Justice , 3 ( 2 ), 132 – 150 .

Grasmuck et al., 2009 Grasmuck , S. , Martin , J. , & Zhoa , S. ( 2009 ). Ethno-racial identity displays on Facebook . Journal of Computer-Mediated Communication , 15 ( 1 ), 158 – 188 . doi: 10.1111/j.1083-6101.2009.01498.x

Hall, 1980 Hall , S. ( 1980 ). Culture, media and language . London : Hutchinson . doi: 10.4324/9780203381182

Holman et al., 2013 Holman , E. A. , Garfin , D. R. , & Silver , R. C. ( 2013 ). Media's role in broadcasting acute stress following the Boston Marathon bombings . Proceedings of the National Academy of Sciences , 111 ( 1 ), 93 – 98 . doi: 10.1073/pnas.1316265110

Hurst et al., 2000a Hurst , Y. G. , Frank , J. , & Browning , S. L. ( 2000a ). How kids view cops: The nature of juvenile attitudes toward the police . Journal of Criminal Justice , 28 ( 3 ), 189 – 202 . doi: 10.1016/S0047-2352(00)00035-0

Hurst et al., 2000b Hurst , Y. G. , Frank , J. , & Browning , S. ( 2000b ). The attitudes of juveniles toward the police: A comparison of black and white youth . Policing: An International Journal of Police Strategies & Management , 23 , 37 – 53 . doi: 10.1108/13639510010314607

Hurst et al., 2005 Hurst , Y. G. , McDermott , M. J. , & Thomas , D. L. ( 2005 ). The attitudes of girls toward the police: Differences by race . Policing: An International Journal of Police Strategies & Management , 28 ( 4 ), 578 – 593 . doi: 10.1108/13639510510628677

Kohm et al., 2012 Kohm , S. A. , Waid-Lindberg , C. A. , Weinrath , M. , Shelley , T. O. , & Dobbs , R. R. ( 2012 ). The impact of media on fear of crime among university students: A cross-national comparison . Canadian Journal of Criminology and Criminal Justice , 54 ( 1 ), 67 – 100 . doi: 10.3138/cjccj.2011.E.01

Lee, 2011 Lee , E. B. ( 2011 ). Young, Black, and connected: Facebook usage among African American college students . Journal of Black Studies , 43 ( 3 ), 336 – 354 . doi: 10.1177/0021934711425044

Lee et al., 2015 Lee , J. , Lim , H. , & Lee , H. ( 2015 ). Differential social distance and confidence in the police . International Journal of Police Science & Management , 17 ( 3 ), 147 – 154 . doi: 10.1177/1461355715596305

Leiber et al., 1998 Leiber , M. J. , Nalla , M. K. , & Farnworth , M. ( 1998 ). Explaining juveniles' attitudes toward the police . Justice Quarterly , 15 ( 1 ), 151 – 174 . doi: 10.1080/07418829800093671

Lim, 2015 Lim , H. ( 2015 ). Social modeling effects on perception of the police: Focus on indirect police contact experience among college students . Policing: An International Journal of Police Strategies & Management , 38 ( 4 ), 675 – 689 . doi: 10.1108/PIJPSM-02-2015-0018

Maxwell, 1996 Maxwell , J. A. ( 1996 ). Qualitative research design: An interactive approach . Thousand Oaks, CA : Sage Publications, Inc .

Nhan, 2019 Nhan , J. ( 2019 ). Issues and controversies in policing today . Lanham, MD : Rowman & Littlefield .

Novich and Hunt, 2016 Novich , M. , & Hunt , G. ( 2016 ). “Get off me”: Perceptions of disrespectful police behaviour among ethnic minority youth gang members . Drugs: Education, Prevention and Policy , 24 ( 3 ), 248 – 255 . doi: 10.1080/09687637.2016.1239697

Papachristos et al., 2012 Papachristos , A. V. , Braga , A. A. , & Hureau , D. M. ( 2012 ). Social networks and the risk of gunshot injury . Journal of Urban Health , 89 ( 6 ), 992 – 1003 . doi: 10.1007/s11524-012-9703-9

Presser and Sandberg, 2015 Presser , L. , & Sandberg , S. ( 2015 ). Narrative criminology understanding stories of crime . New York, NY : NYU Press .

Reisig and Correia, 1997 Reisig , M. D. , & Correia , M. E. ( 1997 ). Public evaluations of police performance: An analysis across three levels of policing . Policing: An International Journal of Police Strategies and Management , 20 ( 2 ), 311 – 325 . doi: 10.1108/13639519710169153

Rosenbaum et al., 2005 Rosenbaum , D. P. , Schuck , A. M. , Costello , S. K. , Hawkins , D. F. , & Ring , M. K. ( 2005 ). Attitudes toward the police: The effects of direct and vicarious experience . Police Quarterly , 8 ( 3 ), 343 – 365 . doi: 10.1177/1098611104271085

Silverman, 2006 Silverman , D. ( 2006 ). Interpreting qualitative data: Methods for analysing talk, text and interaction . London : Sage Publications .

Smith and Anderson, 2018 Smith , A. , & Anderson , M. ( 2018 ). Social media use 2018: Demographics and statistics . Washington, DC : Pew Research Center .

Tyler, 2002 Tyler , T. R. ( 2002 ). A national survey for monitoring police legitimacy . Justice Research and Policy , 4 ( 1–2 ), 71 – 86 . doi: 10.3818/JRP.4.1.2002.71

Tyler, 2006 Tyler , T. R. ( 2006 ). Why people obey the law . Princeton, NJ : Princeton University Press .

Tynes et al., 2019 Tynes , B. M. , Willis , H. A. , Stewart , A. M. , & Hamilton , M. W. ( 2019 ). Race-related traumatic events online and mental health among adolescents of color . Journal of Adolescent Health , 65 ( 3 ), 371 – 377 . doi: 10.1016/j.jadohealth.2019.03.006

Weitzer, 2002 Weitzer , R. ( 2002 ). Incidents of police misconduct and public opinion . Journal of Criminal Justice , 30 ( 5 ), 397 – 408 . doi: 10.1016/S0047-2352(02)00150-2

Weitzer and Tuch, 1999 Weitzer , R. , & Tuch , S. A. ( 1999 ). Race, class, and perceptions of discrimination by the police . Crime & Delinquency , 45 ( 4 ), 494 – 507 . doi: 10.1177/0011128799045004006

Wu, 2013 Wu , Y. ( 2013 ). Race/ethnicity and perceptions of police: A comparison of White, Black, Asian, and Hispanic Americans . Policing and Society , 24 ( 2 ), 135 – 157 . doi: 10.1080/10439463.2013.784288

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• > Journals
• > Social Policy and Society
• > Volume 17 Issue 2
• > The Police Use of Social Media: Transformation or Normalisation?

Article contents

Introduction, internet, social media and democratic policing, research design and methodology, the dynamics of police-citizen communication on social media, the police use of social media: transformation or normalisation.

Published online by Cambridge University Press:  18 April 2017

There has been optimism that social media will facilitate citizen participation and transform the communication strategies of public organisations. Drawing on a case study of the public police in England, this article considers whether social media are transforming or normalising communications. Arguing that social media have not yet served to facilitate interaction between constabularies and citizens in the ways that have been proposed and desired, the article considers factors that structure the transformative potential of social media. It is argued that the uses of social media are mediated by the existing organisational and occupational concerns of the police. This article reveals how an interplay of organisational, technological and individual and cultural dynamics come together to shape how social media are used in constabularies. Embedding social media into police communications is challenging and the technology itself will not bring about the organisational and cultural changes needed to transform police–citizen engagement.

Social media have been heralded as a way of engendering openness, transparency and citizen participation in public policing. Relatively little is known, however, about how social media are understood by officers and staff and incorporated into their communication strategies, and how social media function to facilitate, or otherwise, citizen participation (Brainard and McNutt, Reference Brainard and McNutt 2010 ; Crump, Reference Crump 2011 ; Schneider, Reference Schneider 2016 ). This is important because it is understood that the impact of new technologies in the police environment is contingent on a range of internal and external driving forces and counter forces (Chan, Reference Chan and Newburn 2003 ). Indeed, studies have revealed that social media are not currently transforming the communicative practices of police services in the ways that proponents have proposed (Brainard and McNutt, Reference Brainard and McNutt 2010 ; Crump, Reference Crump 2011 ; Lieberman et al ., Reference Lieberman, Koetzle and Sakiyama 2013 ; Grimmelikhuijsen and Meijer, Reference Grimmelikhuijsen and Meijer 2015 ). This article examines the nature of police communication on social media and the factors which shape their transformative potential. Drawing on Manning ( Reference Manning, Tonry and Morris 1992 , Reference Manning 2008 ), it is argued that the police use of social media is mediated by organisational and occupational concerns. The contribution of this article lies in its explication of the ways that social media have been understood by officers and incorporated into policing routines. In so doing, the ways that the transformative potential of social media have been muted are revealed. I start by exploring the communicative practices of the public police and situating social media within them.

The impetus for initiatives in e-democracy can be traced to the early 1990s, the era when internet use started to proliferate throughout the Western world (Chadwick and May, Reference Chadwick and May 2003 ; Wright, Reference Wright 2006 ; Chadwick, Reference Chadwick 2009 ; Ellison and Hardey, Reference Ellison and Hardey 2014 ). There was, at this time, optimism that the internet might revive democratic structures. Optimism which can be understood in the context of a purported ‘crisis of democracy’, a democratic deficit characterised by low citizen participation in political institutions and declining trust (Stoker, Reference Stoker 2006 ; Wright, Reference Wright 2006 ; Whiteley, Reference Whiteley 2012 ). Oft-framed as a means of reviving ‘Athenian’ participatory democracy Web 1.0, the first stage in the evolution of the World Wide Web (WWW), was certainly hailed by some as a way of reinvigorating decision-making. As empirical work started to reveal that officials and politicians were reluctant to adopt the burgeoning online tools, that citizen participation was low and, that rather than offering new avenues for participation, was attracting those who were already engaged in political processes, early optimism was gradually replaced by a degree of pessimism (Chadwick and May, Reference Chadwick and May 2003 ; Di Gennaro and Dutton, Reference Di Gennaro and Dutton 2006 ; Wright, Reference Wright 2006 ; Chadwick, Reference Chadwick 2009 ; Loader and Mercea, Reference Loader and Mercea 2011 ). Since these early days the capacity of the internet to engender interaction and debate between citizens, officials and politicians has been transformed by the diffusion of Web 2.0 platforms. Emphasising user-generated content, these social media are founded in, and support the principles of, openness and transparency, and, in principle at least, facilitate dialogue, collaboration and co-creativity between users (Macnamara and Zerfass, Reference Macnamara and Zerfass 2012 ; Lipschultz, Reference Lipschultz 2015 ). There has been new waves of optimism that networks such as Facebook, Twitter, YouTube, Snapchat along with Wikies and the blogosphere will facilitate dialogue and debate between citizens, officials and politicians and come to revive political structures (Loader and Mercea, Reference Loader and Mercea 2011 ; Ellison and Hardey, Reference Ellison and Hardey 2014 ; Loader et al ., Reference Loader, Vromen and Xenos 2014 ). As Ellison and Hardey ( Reference Ellison and Hardey 2014 : 26) put it ‘the extraordinary spread of internet usage combined with the changing practices of use – specifically social networking – suggests that there is now serious future potential for the enhancement of online participation’. Such optimism translates into public policing, for reasons I will briefly consider.

There has been systemic pressure on constabularies to facilitate openness, transparency and citizen participation in police decision-making. From smoothing ruptures between the police and citizens (Scarman, Reference Scarman 1981 ; Lea and Young, Reference Lea and Young 1993 ; Sklansky, Reference Sklansky 2005 ), to implanting business principles into decision-making (Loader, Reference Loader 1999 ; Loader and Walker, Reference Loader and Walker 2001 ; Bullock, Reference Bullock 2014 ), to providing a means through which citizens can express their preferences for the nature of crime control at the local level (McLaughlin; Reference McLaughlin 2005 ; Bullock, Reference Bullock 2014 ), opening up constabularies has been viewed as a way of protecting citizens, improving the quality of the service and initiating a means of holding officers to account. It follows that constructing constabularies as open, transparent and democratic has been a primary aim of contemporary police communication strategies. There have been a number of reasons for promoting citizen participation in public policing. However, following Scarman ( Reference Scarman 1981 ), historically one form of consultative practice has dominated: the police-community meeting. Whilst omnipresent, many studies have revealed that police–community meetings have done little to transform police communication. Police–community meetings have suffered from low participation, those citizens who did participate were typically white, middle-class and already embedded in the political establishment, and meetings have generally provided a forum for officers to broadcast information and to rubber stamp decisions that had already been made by constabularies rather than to stimulate debate and dialogue between officers and citizens (Keith, Reference Keith 1988 ; Stratta, Reference Stratta 1990 ; Hughes, Reference Hughes 1994 ; Elliott and Nicholls, Reference Elliott and Nicholls 1996 ; Harfield, Reference Harfield 1997 ; Jones and Newburn, Reference Jones and Newburn 2001 ; Myhill et al ., Reference Myhill, Yarrow, Dalgleish and Docking 2003 ). In short, traditional forms of community engagement activity have done little to promote the desired outcomes of increased participation, transparency and accountability.

Moving police communication from the physical to the virtual, social media have been presented as a way of circumnavigating the aforementioned problems and affording a mechanism through which constabularies might engage with citizens and communities and, in so doing, present themselves as open, participative and democratic (Fink and Zerfass, Reference Fink and Zerfass 2010 ; Avery and Graham, Reference Avery and Graham 2013 ). The use of social media by constabularies to engage with citizens and other constabularies has been a marked trend in recent years. This trend is best understood within the context of the reinvigoration of community policing in the UK and around the globe. The practices of community policing seek to facilitate interaction between police officers and citizens. In the interests of promoting legitimacy and controlling crime, the aim of community policing is to encourage citizens to take individual and collective responsibility for crime control at the local level and to marry policing and community priorities (Manning, Reference Manning, Greene and Mastrofski 1991 ; Barlow and Barlow, Reference Barlow and Barlow 1999 ; Maguire and Wells, Reference Maguire, Wells and Giles 2002 ; Bullock, Reference Bullock 2014 ). It follows that social media have been adopted by community policing teams across the USA, Australia and Northern Europe (COPS, 2013 ; The Police Foundation, Reference Foundation 2014 ). Indeed, of the some 2,000 official police Twitter accounts operating in the UK at the time of writing about half are thought to be community policing accounts ( Reference Ashby Ashby, n.d .). Thus community policing teams are supposed to use social media to reach out to citizens and communities, to engage them in debate and to listen to and act upon their concerns. It has been hoped that social media will provide an efficient technological response to an enduring conundrum in public policing – that of how to stimulate communication between officers and citizens.

For all the optimism that social media will expedite dialogue and debate between citizens and officers, large-scale analyses of social media content have started to demonstrate that police communication on social media is one-way (Brainard and McNutt, Reference Brainard and McNutt 2010 ; Crump, Reference Crump 2011 ; Lieberman et al ., Reference Lieberman, Koetzle and Sakiyama 2013 ; Grimmelikhuijsen and Meijer, Reference Grimmelikhuijsen and Meijer 2015 ). Research has indicated that social media are primarily used by constabularies to make requests for assistance, to circulate police-relevant crime and incident information and to give crime prevention tips rather than to facilitate interaction, debate and collaborative problem-solving. Observations which fall in line with research from the public (Wright, Reference Wright 2006 ; Avery and Graham, Reference Avery and Graham 2013 ; Ellison and Hardey, Reference Ellison and Hardey 2014 ) and private (Jones et al ., Reference Jones, Ravid and Rafaeli 2004 ; Preece et al ., Reference Preece, Nonnecke and Andrews 2004 ; Joyce and Kraut, Reference Joyce and Kraut 2006 ) spheres more generally. The qualitative research on which this article is based did not systematically quantify the nature of police generated social media. It is worth briefly noting, however, that the reflections of participants broadly chimed with this wider body of evidence. Asked to reflect on this matter, participants revealed a degree of complexity. They drew attention to how the aim of using social media certainly was to transcend one-way communication in principle and some participants were adamant that social media could facilitate police–citizen interaction, and gave examples of this occurring in practice. Reflecting observations that the Internet might enable citizens to forge direct links with officials and in so doing engender transparency and foster forms of accountability which would not have been previously been attainable (Loader and Mercea, Reference Loader and Mercea 2011 ; Ellison and Hardey, Reference Ellison and Hardey 2014 ; Loader et al ., Reference Loader, Vromen and Xenos 2014 ), some participants also thought that social media could improve officer responsiveness to the concerns of citizens. Even so, reflecting either on their own experiences or those of others, many participants drew attention to how this represented the exception rather than the rule, and were sometimes rather pessimistic about what could realistically be achieved.

In sum, the weight of research is indicating that social media are not transforming the nature of routine police–citizen communications. Indeed, research has demonstrated that new technologies have had less effect on police practices than has been advocated (a result of how they are mediated by the existing organisational and occupational concerns of the police) and that the impact of police technologies can be to reproduce existing orders rather than to produce changes (Manning, Reference Manning, Tonry and Morris 1992 , Reference Manning 2008 ). Technology at once shapes organisations and occupations and is shaped by them (Manning, Reference Manning, Tonry and Morris 1992 ; Chan, Reference Chan and Newburn 2003 ). As Chan ( Reference Chan and Newburn 2003 ) notes, technological changes should be understood via an interpretative rather than deterministic lens. An interpretative lens highlights how organisational members and the organisational context influences the use of technologies, as they are introduced into organisations in ways that are not always easy to predict. Thus, the way technology is used in police organisations is influenced by the nature of the technology itself, the meaning officers and staff ascribe to technology and wider organisational processes and practices. Consideration of these matters as they apply to the introduction of social media into the communication practices of constabularies is the primary aim of this article. Let us turn our attention now to the design and parameters of the present study.

This article draws on the analysis of thirty-two interviews conducted with officers and police staff in five constabularies in England in 2014. These participants were generated through purposive sampling. As ‘key informants’ (Parsons, Reference Parsons and Lavrakas 2008 ), participants were known to have experience and knowledge of social media and the way that they are understood and employed by constabularies and officers. Participants fell into three broad groups. The first group ( N = 10) comprised officers and staff who had made use of social media over a period of time. Often pioneers within their organisation, they were typically early adopters of social media who had experimented extensively with it. The second group ( N = 10) held relevant police managerial roles at the local and/or national level for social media and/or community policing. The third group ( N = 12) comprised communications and public relations (PR) professionals. These participants managed and coordinated physical and virtual communications on behalf of constabularies and were responsible for developing the infrastructure to do so. Participants were identified through a two-fold approach. First, through ‘snowball sampling’ (Chromy, Reference Chromy and Lavrakas 2008 ). Existing participants nominated additional participants from among their networks of colleagues and connections. Second, an advert was placed on a College of Policing online collaboration tool that enables knowledge and information sharing across constabularies in England and Wales. Footnote 1 Participants were asked to reflect on the organisational benefits generated through social media and the factors which shaped their use. Themes were teased out and are discussed in the forthcoming sections in light of extant literature from both the public and private sectors. Following the aforementioned connection between community policing and social media, focus was on the role of the latter in facilitating citizen engagement as opposed to their role in the generation of intelligence or police investigations (see COPS, 2013 ). The article also focuses on the official, rather than personal, use of social media (see Goldsmith, Reference Goldsmith 2015 ; Schneider, Reference Schneider 2016 ). The emphasis is on police use of Twitter. This emphasis was not intentional; however, it soon became clear that Twitter was the primary platform used by officers and staff – something which has implications for the nature of communication, as this article will demonstrate. Let us now consider how the interaction of organisational, technological, and individual and cultural dynamics influence the nature of police–citizen communication on social media and the implications for the transformative potential of social media.

Organisational dynamics

Taken together, a series of organisational dynamics – which included (1) the attitudes and approach of police leaders (2) organisational responses to risk (3) strategy and (4) the nature of the infrastructure established to support users of social media – have influenced how officers use social media. Matters which are unpicked in the forthcoming sections.

Accounts indicated that the way that police officers use social media to communicate with citizens is influenced by the attitudes and approach of police leaders. Where chief officers are supportive of officer use of social media as a communicative tool, and, pertinently, where they are proactively exploiting and promoting social media themselves, application by the rank and file was thought to be stimulated. Participants reported that such sponsorship by chief officers acts to subdue any fears that officers may have about communicating in this way, and reinforces the principle that social media should form an integral part of contemporary police communications. However, accounts also indicated that whilst some police leaders were supportive of officer use of social media and utilised social media themselves to communicate with citizens, such support and application were not unanimous (see also Crump, Reference Crump 2011 ). Instead, accounts indicated that some leaders were cautious about officer use of social media or, indeed, opposed their routine use. Whilst the perspectives of chief officers were not incorporated into this research, participants indicated that opposition is born of lack of clarity about the value of social media within the organisation and concerns about organisational risk. In respect of the former, the accounts of participants indicated that some chief officers struggle to see a role for social media within the organisation, perhaps because they are unfamiliar with the relatively new and ever-evolving technology. More specifically, participants indicated that some chief officers may view social media as a time consuming distraction for officers and staff, a concern widely shared by senior managers in other organisations (Fink and Zerfass, Reference Fink and Zerfass 2010 ). Jovial comments such as ‘you can get obsessed with it’ (INT18) and ‘it can take over your life’ (INT23) notwithstanding, it is worth noting that participants stated that using Twitter was not generally time consuming for officers. This is a function of the configuration of the technology and the way it is used by officers and staff. In respect of the latter, accounts strongly suggested that concerns about security and reputational risk are commonly expressed by chief officers. From disclosing sensitive or personal information obtained by constabularies, to divulging operational tactics, to revealing thoughtless or even offensive attitudes, social media potentially pose risks to the security, effectiveness and reputation of constabularies and officers therein (ACPO, 2013 ; Goldsmith, Reference Goldsmith 2015 ). Whilst participants indicated that complaints about the nature of communication on official social media channels are unusual, they also drew attention to how concerns about risk are nevertheless pervasive, a point that is considered in more detail below.

Research has demonstrated that there are tensions within public and private organisations regarding the role of social media (Avery and Graham, Reference Avery and Graham 2013 ; Fink and Zerfass, Reference Fink and Zerfass 2010 ; Macnamara and Zerfass, Reference Macnamara and Zerfass 2012 ). On the one hand, social media have been widely held to be a way of promoting the dissemination of information and increasing the ability of organisations to interact with ‘consumers’ in novel ways. On the other hand, it is difficult for organisations to control who uses social media and the nature of the content disseminated on them. This lack of control underscores the widely held concern that social media present organisational risk. Indeed, because corporate reputation is viewed as fragile and easily damaged by any scandal and misconduct revealed on social media, loss of control of messages is seen as a major risk by communications and PR professionals (Fink and Zerfass, Reference Fink and Zerfass 2010 ; Macnamara and Zerfass, Reference Macnamara and Zerfass 2012 ; Lee and McGovern, Reference Lee and McGovern 2013 ). Whilst such concern seems to be widespread, it might be compounded in constabularies. This is because the communications practices of constabularies have traditionally been tightly proscribed, in the context that officers are entrusted with upholding the law and officers are bound by legal and procedural regulations (Brainard and McNutt, Reference Brainard and McNutt 2010 ; Lee and McGovern, Reference Lee and McGovern 2013 ).

The ways that the police organisation responds to this tension influences the nature of communication on social media. Participants in the present study noted that communications and PR officials apply, or seek to apply, ‘different levels of organizational control and laissez faire’ (INT5). This control is most clearly revealed in the decisions regarding who has access to which kinds of official police Twitter accounts. Community policing Twitter accounts tend to be established and operated either on behalf of named, clearly identifiable individuals or on behalf of teams of officers. Fundamentally aimed at controlling communications and reducing risk, some communications officials do not allow officers to set up individual official Twitter accounts, or alternatively they tightly restrict access to them. The more anonymous team accounts are preferred by some communications and PR officials because – operated by a collective rather than an individual – they are seen to afford the organisation a greater degree of control. Since communication via social media can falter when officers move vertically or horizontally within the organisation, they also facilitate a degree of continuity of communication over time. Restricting access to individual accounts has been seen as a way of resolving the dilemma of ‘succession planning’. Exerting such control has, however, influenced the timbre of communications. Participants consistently drew attention to how the ‘personal’ communication associated with the individual accounts may be effective in engaging citizens in ways that the ‘corporate’ communication more associated with the team accounts may not. Many participants in the present study agreed that to facilitate engagement, communicative practices should be pushed down to the micro level. However, they also accepted that doing so might represent a risk for the organisation as it would be less able to control the content of communication. Accordingly, there would seem to be a tension between a need for organisational control of communications and the generation of engaging content that leads to citizen participation.

Strategy is a further organisational feature which has shaped the development of officer use of social media and influenced the nature of communicative practices. Constabularies in the UK began experimenting with Twitter in 2008, experiments which were initially associated with entrepreneurial individuals who received varying degrees of official support (Crump, Reference Crump 2011 ). Participants in the present study agreed that the use of social media grew organically with little direction and that the strategies to structure the use of social media followed, rather than informed, their development. ‘It felt like the right thing to do so we went on and did it, after we did it and learnt lessons we went back and properly put a formal strategy in place’, noted one participant (INT10). Indeed, limited strategic direction has characterised the development and use of the internet by private and public organisations more widely (Wright, Reference Wright 2006 ; Macnamara and Zerfass, Reference Macnamara and Zerfass 2012 ; Avery and Graham, Reference Avery and Graham 2013 ). This ‘improvised’ approach may start to explain why the overall objectives of utilising social media are not always clear and, in fact, seem at times to be in conflict with one another. It also starts to explain why there is a great deal of variation – in terms of organisational expectations of social media, individual capacity to engage with the technology and the quality and pitch of the content – between and within constabularies, as the technology is understood and applied differently by officers and staff who enjoy more, or less, organisational support and access to resources.

Certainly, the availability and quality of support for officers who wish to engage citizens via social media have played a role in shaping their use. Previous research has demonstrated that infrastructure – for instance supervision and training – to support technological innovation within police organisations has often been missing (Manning, Reference Manning 2001 ). Reflecting this, the infrastructure to support officer's use of social media was generally thought to be weak. Whilst policies, guidance and training are available, accounts of participants in the present study indicated that they have been of limited use in influencing how officers understand and use social media. The result is that officers learn how to communicate on social media experientially through ‘trial and error’ (INT9). These observations echo the experiences of users of social media in other organisations (Macnamara and Zerfass, Reference Macnamara and Zerfass 2012 ). In fact, the situation might be somewhat inevitable. Whilst officers and staff clearly ask for guidance, participants tended to agree that it is difficult for the organisation to provide the formal guidance needed. Participants drew attention to the intuitive nature of social media, which is generally guided by instinct rather than formal instruction (see also Schmidt, Reference Schmidt, Weller, Bruns, Burgess, Mahrt and Puschmann 2013 ). Guiding officers towards good practice in an ever-changing virtual world is clearly challenging. Moreover, doing so might actually influence the tone of communication on social media. Participants drew attention to a risk that over prescription will produce monotonous communication, which itself does little to engage citizens.

Technological dynamics

The Information Communications and Technology (ICT) infrastructure, cultures of ICT departments and the dominant social media platform utilised by constabularies and officers have all played a role in shaping the nature of communication on social media. Participants in the present study drew attention to how police ICT are chronically under resourced and that the introduction of social media platforms, which are generally free, open and require light programming, is at odds with the established culture of ICT development within constabularies which tends to be cautious, security conscious and highly risk adverse (see also Crump, Reference Crump 2011 ; London Assembly, Reference Assembly 2013 ). A consequence is that officers have limited access to both static and mobile ICT at work – a situation which participants indicated can undermine the routine use of social media (see also London Assembly, Reference Assembly 2013 ). Access to mobile ICT was thought by participants to be particularly important in the community policing context. To use social media in an office environment was thought to distract officers from the raison d'etre of their role – to be visible and available in the community engaging with citizens – and to undermine its value as a communication tool. Indeed, participants indicated that where officers are not able to communicate on social media whilst out of the office environment, they are less likely to do so at all. Given that at the present time many officers do not have access to official mobile technology, participants indicated that the use of personal devises was common. In fact, participants drew attention to what was sometimes seen as a paradoxical situation. Whilst officers have become used to utilising mobile ICT in many ways within their private lives, this did not readily translate into their working lives (see also Tanner and Meyer, Reference Tanner and Meyer 2015 ). In turn, participants drew attention to how any investment in mobile ICT by constabularies (and some have invested) paid dividends for officers.

The dominant platform used by officers and staff – Twitter – also shapes the nature of police communication and its transformative potential. Twitter certainly supports dialogue and deliberation in principle (Halavais, Reference Halavais, Weller, Bruns, Burgess, Mahrt and Puschmann 2013 ; Schmidt, Reference Schmidt, Weller, Bruns, Burgess, Mahrt and Puschmann 2013 ). However, participants suggested that Twitter was not necessarily conducive to police–citizen interaction and collaboration in practice, especially when compared with other social media platforms (see also Crump, Reference Crump 2011 ). This is because Twitter – which facilitates the dissemination of short (140-character) messages – is thought to be better suited to ‘broadcasting’ police relevant information than facilitating interaction between officers and citizens (see also Crump, Reference Crump 2011 ). Given that community policing teams have been expected to use social media to engender engagement, this raises questions about why Twitter has become so dominant. Its dominance might result from the failure to situate police use of social media within an overarching communications strategy and from the limitations of the police ICT infrastructure. However, a primary explanation for the dominance of Twitter lies in its manageability for officers and staff, especially when compared to other platforms. Twitter appears to have become the preferred platform less because of its value as an engagement tool and more because it is straightforward and relatively quick for officers to use. There is a risk that establishing networks of Twitter accounts has become an end in itself rather than a means to an end. Indeed, it was generally accepted by participants in the present study that other platforms, notably Facebook, could be more effective for generating the desired interaction between officers and citizens. However, Twitter was seen to be quick to use and much more manageable for officers. Thus, participants drew attention to a fundamental contradiction. Due to their configuration and features, social media platforms other than Twitter (notably Facebook) may offer more effective ways of promoting engagement and citizen participation. Conversely, it is these very features that render the alternative(s) time-consuming for officers and explain why their use is discouraged by constabularies.

It is worth noting at this juncture that a focus on Twitter may be limiting the scope of police communication. This is because there are differences in the reach and demographic profile of the users of different platforms. At the time of writing, Facebook has a much greater reach than does Twitter. To illustrate, research has shown that nearly all citizens who have a profile on social media (96 per cent) have one on Facebook, whereas, in contrast, 30% of social networkers say they have a Twitter profile (Ofcom, 2014 ). In addition, there are differences between platforms in respect of the social and demographic characteristics of their users. For example, adult Twitter users are better off and better educated than both non-users of social media and users of other platforms (Rainie et al ., Reference Rainie, Smith, Lehman Schlozman, Brady and Verba 2012 ). Whilst adult users of Facebook vary little by age and gender, adult Twitterers are younger and more likely to be male than female (Ofcom, 2014 ). In addition, Twitter is poorly used by UK teenagers. For instance, Lenhart ( Reference Lenhart 2015 ) found that thirteen- to seventeen-year olds reported that they used Facebook most frequently (41 per cent), followed by Instagram (20 per cent) and Snapchat (11 per cent). A mere 6 per cent reported that they used Twitter most often. A primary benefit of social media, much discussed in policing discourse, is their presumed ability to attract the youthful audience, which has conventionally been difficult to engage. Any hope of doing so might be undermined by a concentration of communication on Twitter.

In sum, these observations draw attention to how, by concentrating their communication on Twitter, community policing teams may inadvertently be narrowing their reach towards an audience which is dominated by the better educated, better off, younger adult males. These observations also draw attention to the importance of varying communication practices on social media to maximise their potential reach and of being attentive and responsive to the ever-evolving trends in social media use. Social media use is not stable. As Wright ( Reference Wright 2006 : 57) put it ‘technology, and people's interaction with it, evolves very, very quickly and things change’. This point was in fact acknowledged by some of the participants in the present study – notably the communications and PR professionals – and as a consequence some constabularies are experimenting with different platforms at the organisational level at least. Nonetheless, community policing teams, and the officers within these teams, largely confine their communications on Twitter with inevitable implications for the reach of their communication practices.

Individual and cultural dynamics

Lastly, I turn to how individual preferences and cultural features of the police organisation shape the use of social media. Participants drew attention to how some officers and staff are more effective communicators than are others. Whilst it might be that some officers can learn tricks to help them communicate effectively, be it formally or experientially, time and time again participants drew attention to how the successful Twitter accounts were essentially driven by personalities. Indeed, participants indicated that social media use is likely to be valuable only where officers and staff are personally motivated to invest time in generating engaging content. This is in part a function of individual preferences and proficiencies – some officers are naturally better communicators than are others and this applies to offline and online settings. However, participants indicated that officers and staff are differently motivated to engage with social media. There clearly remains some resistance to using social media at the individual officer level. Resistance may be the result of anxiety born of the organisational risks discussed above. Given that participants suggested that senior officers may be more confident in communicating on social media than the rank and file, this is something that might be influenced by rank. This is a slightly ironic position. It is the community policing teams who are expected to use social media to communicate, yet they are comprised of the lowest ranking officers who are little supported in their use of social media. In addition, whilst many officers are no doubt used to using social media in their private lives, using them in their professional lives will represent a change for many. And organisational changes might be resisted. One participant concluded that ‘it's about shifting attitudes and getting people to understand what it is all about’ (INT30). That some officers do not ‘understand what it is all about’, links to the lacklustre response from (some) chief officers, the lack of clear organisational strategy and the lack of high-quality instruction – all noted above. However, there might well be wider cultural factors at play here, a theme on which I finish.

Many studies have demonstrated that officers are sceptical regarding the view that community engagement should play a prominent role within police work (e.g. Fielding, Reference Fielding, Newburn and Stanko 1994 ; Greene, Reference Greene 2000 ; Herbert, Reference Herbert 2001 ; Bullock, Reference Bullock 2014 ). The rationale for and practices associated with community collaboration are at odds with the rationale of – and practices that officers tend to associate, rightly or wrongly, with – ‘real’ police work: namely, the pursuit and arrest of criminal suspects and the enforcement of the criminal law (Skolnick, Reference Skolnick 1966 ; Fielding, Reference Fielding, Newburn and Stanko 1994 ; Greene, Reference Greene 2000 ). Social media catapults police–citizen engagement from the physical into the virtual realm. This changes the mechanism of delivery, but there is no reason to assume that the attitudes of officers towards the activity itself will be altered. It may well be that social media are resisted by some officers because of wider resistance to the activity social media are seen to represent – citizen engagement. As one participant explained: ‘historically there has been some scepticism . . . a nice woolly, fluffy thing to do but what is the point?’ (INT15). In fact, participants drew attention to how for many officers ‘the point’ of incorporating social media into police communications is to promote crime control rather than to promote improved relations with citizens. Whilst the official police use of social media is often situated within discourses which foreground community engagement and collaboration, the rank and file may see any benefits rather differently. Certainly when reflecting on their own views, or on the views of others, participants indicated that the organisational benefit of investing officer time in social media is derived less from its potential to promote community-oriented benefits and more from its potential to generate police-oriented benefits: ‘it's all about building rapport . . . that is just day-to-day stuff but [it] really comes into its own when [you] need something’ (INT2). This extract illustrates how the participants in the present study suggested that for many officers the potential to generate information that might promote the enforcement of the criminal law or promote other police relevant outcomes represented the real organisational value of investing in social media. It follows that where social media could be shown to be of value in facilitating law enforcement, its profile was heightened. To illustrate, many participants drew attention to how quantifying the amount of police relevant information that was generated through social media channels, together with the number of arrests and subsequent criminal convictions, was important for demonstrating their value. Social media represent a change in communication style with which some in the organisation are clearly uncomfortable. Moreover, perhaps, they represent a practice that some do not see as a policing priority.

Social media have been presented as a way of facilitating citizen participation in public policing. British constabularies have long sought but often struggled to engage citizens, and social media have been seen as a tool for circumventing past problems and providing new mechanisms through which to present the institution as open, transparent and democratic. This article adds to the growing body of work which indicates that for all the potential of social media, much output is one-way and fails to facilitate interaction between constabularies and citizens. We can say with some confidence that whilst omnipresent, social media are not inevitably transformative. This article considered the factors which shape the police use of social media in order to shed light on why they may not be transforming police communicative practices in the ways that have been mooted.

Whilst technology is oft-promoted as a way of increasing police effectiveness and efficiency, technological advances in policing have little changed the character of policing or its effectiveness (Manning, Reference Manning, Tonry and Morris 1992 , Reference Manning 2001 , Reference Manning 2008 ; Chan, Reference Chan and Newburn 2003 ). Policing remains a low-technology occupation, technology is likely to be underutilised by officers, and police technologies tend to reproduce existing orders rather than transform them (Manning, Reference Manning 2008 ). Pertinently, technology shapes organisations and is shaped by them, and, in this sense, the introduction of a new technology is merely the beginning of a ‘technological drama’ which involves processes of normalisations, adjustment, reconstitution and reintegration (Chan, Reference Chan and Newburn 2003 : 673). In this vein, this article has drawn attention to how the transformative potential of social media has been mediated by the ways that organisations and individuals within them interpret the technologies and incorporate them into their day-to-day routines. As social media are introduced into constabularies their transformative potential are shaped by the organisational environment. This article has demonstrated that this can be understood in terms of an interplay between technological, organisational and individual and cultural dynamics. From the standpoint of police leaders, to the approach taken to organisational risk, to the nature of strategic direction, to the quality of training and guidance, to the availability and nature of police ICT, to the peculiarities of the dominant social media platforms utilised, to the attitudes of rank and file officers, a wide range of leadership, managerial, technological and cultural dynamics have played a role in shaping what has been achieved. Taken together then, these dynamics demonstrate that social media represent not just a technological revolution but an organisational and cultural revolution that must be negotiated by organisations and individuals.

This article demonstrates that social media have not been absorbed into police communication practices in a straightforward way. The scepticism and risk aversion of some leaders and the apathetic response from some officers indicate that there are at times conflicts between organisational needs and expectations and the conditions required to promote effective communication on social media (see also Macnamara and Zerfass, Reference Macnamara and Zerfass 2012 ). Failure to provide leadership, strategic guidance or to develop an infrastructure (including a technological infrastructure) to support social media use by officers indicates that the role social media should be playing within police communications is not clear and that the degree to which utilising them is seen as an organisational priority is questionable. Furthermore their transformative potential appears to have been muted by the organisational upheavals and conflicts that social media have generated and the ways that constabularies and officers therein have responded. Social media are undoubtedly altering the ways that constabularies and officers communicate with citizens. However, embedding social media into police communications is challenging and the application of the technologies themselves will not bring about the wider organisational and cultural changes needed to transform police–citizen communications.

1 Known as POLKA ‘Police OnLine Knowledge Area’.

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• Volume 17, Issue 2
• Karen Bullock (a1)
• DOI: https://doi.org/10.1017/S1474746417000112

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Successful Practices for using Social Media by Police departments: a Case Study of the Munich Police

• Cigdem Akkaya , J. Fedorowicz , H. Krcmar
• Published in European Conference on… 2019
• Political Science

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Social media use of the police in crisis situations: a mixed-method study on communication practices of the german police, do organizational differences matter for the use of social media by public organizations a computational analysis of the way the german police use twitter for external communication, spreading information or engaging the public the german police’s communication on twitter, construction and dissemination of information veracity on french social media during crises: comparison of twitter and wikipedia, 58 references, the police on twitter: image management, community building, and implications for policing in canada, what are the police doing on twitter social media, the police and the public, social media in emergency management: twitter as a tool for communicating risks to the public, social media strategies: understanding the differences between north american police departments, emergency services' attitudes towards social media: a quantitative and qualitative survey across europe, citizen-government collaboration on social media: the case of twitter in the 2011 riots in england, top 10 u.s. municipal police departments and their social media usage, the social media manifesto: a comprehensive review of the impact of social media on emergency management., social media use by government: from the routine to the critical.

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Social Media Surveillance by the U.S. Government

A growing and unregulated trend of online surveillance raises concerns for civil rights and liberties.

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Social media has become a significant source of information for U.S. law enforcement and intelligence agencies. The Department of Homeland Security, the FBI, and the State Department are among the many federal agencies that routinely monitor social platforms, for purposes ranging from conducting investigations to identifying threats to screening travelers and immigrants. This is not surprising; as the U.S. Supreme Court has  said , social media platforms have become “for many . . . the principal sources for knowing current events, . . . speaking and listening in the modern public square, and otherwise exploring the vast realms of human thought and knowledge” — in other words, an essential means for participating in public life and communicating with others.

At the same time, this growing — and mostly unregulated — use of social media raises a host of civil rights and civil liberties concerns. Because social media can reveal a wealth of personal information — including about political and religious views, personal and professional connections, and health and sexuality — its use by the government is rife with risks for freedom of speech, assembly, and faith, particularly for the Black, Latino, and Muslim communities that are historically targeted by law enforcement and intelligence efforts. These risks are far from theoretical: many agencies have a track record of using these programs to target minority communities and social movements. For all that, there is little evidence that this type of monitoring advances security objectives; agencies rarely measure the usefulness of social media monitoring and DHS’s own pilot programs showed that they were not helpful in identifying threats. Nevertheless, the use of social media for a range of purposes continues to grow.

In this Q&A, we survey the ways in which federal law enforcement and intelligence agencies use social media monitoring and the risks posed by its thinly regulated and growing use in various contexts.

Which federal agencies use social media monitoring?

Many federal agencies use social media, including the  Department of Homeland Security  (DHS),  Federal Bureau of Investigation  (FBI),  Department of State  (State Department),  Drug Enforcement Administration  (DEA),  Bureau of Alcohol, Tobacco, Firearms and Explosives  (ATF),  U.S. Postal Service  (USPS),  Internal Revenue Service  (IRS),  U.S. Marshals Service , and  Social Security Administration  (SSA). This document focuses primarily on the activities of DHS, FBI, and the State Department, as the agencies that make the most extensive use of social media for monitoring, targeting, and information collection.

Why do federal agencies monitor social media?

Publicly available information shows that federal agencies use social media for four main — and sometimes overlapping — purposes. The examples below are illustrative and do not capture the full spectrum of social media surveillance by federal agencies.

Investigations : Law enforcement agencies, such as the FBI and some components of DHS, use social media monitoring to assist with criminal and civil investigations. Some of these investigations may not even require a showing of criminal activity. For example, FBI agents can open an “assessment” simply on the basis of an “authorized purpose,” such as preventing crime or terrorism, and without a factual basis. During assessments, FBI agents can carry out searches of publicly available online information. Subsequent investigative stages, which require some factual basis, open the door for more invasive surveillance tactics, such as the monitoring and recording of chats, direct messages, and other private online communications in real time.

At DHS, Homeland Security Investigations (HSI) — which is part of Immigration and Customs Enforcement (ICE) — is the Department’s “ principal investigative arm .” HSI  asserts  in its training materials that it has the authority to enforce any federal law, and relies on social media when conducting investigations on matters ranging from civil immigration violations to terrorism. ICE agents can look at publicly available social media content for purposes ranging from finding fugitives to gathering evidence in support of investigations to probing “potential criminal activity,” a “threat detection” function discussed below. Agents can also operate undercover online and monitor private online communications, but the circumstances under which they are permitted to do so are not publicly known.

Monitoring to detect threats:  Even without opening an assessment or other investigation, FBI agents can monitor public social media postings. DHS components from ICE to its intelligence arm, the Office of Intelligence & Analysis, also  monitor social media  — including specific individuals — with the goal of identifying potential threats of violence or terrorism. In addition, the FBI and DHS both engage private companies to conduct online monitoring of this type on their behalf. One firm, for example, was  awarded  a  contract  with the FBI in December 2020 to scour social media to proactively identify “national security and public safety-related events” — including various unspecified threats, as well as crimes — which have not yet been reported to law enforcement.

Situational awareness:  Social media  may   provide  an “ear to the ground” to help the federal government coordinate a response to breaking events. For example, a range of DHS components — from Customs and Border Protection (CBP) to the National Operations Center (NOC) to the Federal Emergency Management Agency ( FEMA ) — monitor the internet, including by keeping tabs on a broad list of websites and keywords being discussed on social media platforms and tracking information from sources like news services and local government agencies.  Privacy impact assessments  suggest there are few limits on the content that can be reviewed — for instance, the PIAs list a sweeping range of keywords that are monitored (ranging, for example, from “attack,” “public health,” and “power outage,” to “jihad”). The purposes of such monitoring include helping keep the public, private sector, and governmental partners informed about developments during a crisis such as a natural disaster or terrorist attack; identifying people needing help during an emergency; and knowing about “ threats or dangers ” to DHS facilities.

“Situational awareness” and “threat detection” overlap because they both involve broad monitoring of social media, but situational awareness has a wider focus and is generally not intended to monitor or preemptively identify specific people who are thought to pose a threat.

Immigration and travel screening:  Social media is  used to  screen and vet travelers and immigrants coming into the United States and even to monitor them while they live here. People applying for a range of immigration benefits  also undergo  social media checks to verify information in their application and determine whether they pose a security risk.

How can the government’s use of social media harm people?

Government monitoring of social media can work to people’s detriment in at least four ways: (1) wrongly implicating an individual or group in criminal behavior based on their activity on social media; (2) misinterpreting the meaning of social media activity, sometimes with severe consequences; (3) suppressing people’s willingness to talk or connect openly online; and (4) invading individuals’ privacy. These are explained in further detail below.

Assumed criminality:  The government may use information from social media to label an individual or group as a threat, including characterizing  ordinary activity  (like wearing a particular sneaker brand or making common hand signs) or social media connections as evidence of criminal or threatening behavior. This kind of assumption can have high-stakes consequences. For example, the NYPD  wrongly arrested  19-year-old Jelani Henry for attempted murder, after which he was denied bail and jailed for over a year and a half, in large part because prosecutors thought his “likes” and photos on social media proved he was a member of a violent gang. In another  case  of guilt by association, DHS officials barred a Palestinian student arriving to study at Harvard from entering the country based on the content of his friends’ social media posts. The student had neither written nor engaged with the posts, which were critical of the U.S. government. Black, Latino, and Muslim people are especially vulnerable to being falsely labeled threats based on social media activity, given that it is used to inform government decisions that are often already tainted by bias such as  gang determinations  and  travel screening  decisions.

Mistaken judgments:  It can be difficult to accurately interpret online activity, and the repercussions can be severe. In 2020, police in Wichita, Kansas  arrested  a teenager on suspicion of inciting a riot based on a mistaken interpretation of his Snapchat post, in which he was actually denouncing violence. British travelers were interrogated at Los Angeles International Airport and  sent back  to the U.K. due to a border agent’s misinterpretation of a joking tweet. And DHS and the FBI  disseminated  reports to a Maine-area intelligence-sharing hub warning of potential violence at anti-police brutality demonstrations based on fake social media posts by right-wing provocateurs, which were distributed as a warning to local police.

Chilling effects:  People are highly likely to  censor  themselves when they think they are being watched by the government, and this undermines everything from political speech to creativity to other forms of self-expression. The Brennan Center’s  lawsuit  against the State Department and DHS documents how the collection of social media identifiers on visa forms — which are then stored indefinitely and shared across the U.S. government, and sometimes with state, local, and foreign governments — led a number of international filmmakers to stop talking about politics and promoting their work on social media. They self-censored because they were concerned that what they said online would prevent them from getting a U.S. visa or be used to retaliate against them because it could be misinterpreted or reflect controversial viewpoints.

Loss of privacy:  A person’s  social media presence  — their posts, comments, photos, likes, group memberships, and so on — can collectively reveal their ethnicity, political views, religious practices, gender identity, sexual orientation, personality traits, and vices. Further, social media can reveal more about a person than they intend. Platforms’ privacy settings frequently change and can be difficult to navigate, and even when individuals keep information private it can be disclosed through the activity or identity of their connections on social media. DHS at least has recognized this risk, categorizing social media handles as “sensitive personally identifiable information” that could “result in substantial harm, embarrassment, inconvenience, or unfairness to an individual.” Yet the agency has failed to place robust safeguards on social media monitoring.

Who is harmed by social media monitoring?

While all Americans may be harmed by untrammeled social media monitoring, people from historically marginalized communities and those who protest government policies typically bear the brunt of suspicionless surveillance. Social media monitoring is no different.

Echoing the transgressions of the  civil rights era , there  are   myriad   examples  of the FBI and DHS using social media to surveil people speaking out on issues from racial justice to the treatment of immigrants. Both agencies have monitored Black Lives Matter activists. In 2017, the FBI  created  a specious terrorism threat category called “Black Identity Extremism” (BIE), which can be read to include protests against police violence. This category has been used to rationalize  continued   surveillance  of black activists, including monitoring of social media activity. In 2020, DHS’s Office of Intelligence & Analysis (I&A)  used  social media and other tools to target and monitor racial justice protestors in Portland, OR, justifying this surveillance by pointing to the threat of vandalism to Confederate monuments. I&A then  disseminated  intelligence reports on journalists reporting on this overreach.

DHS especially has  focused  social media surveillance on immigration activists, including those engaged in  peaceful protests  against the Trump administration’s family separation policy and others  characterized  as “anti-Trump protests.” From 2017 through 2020, ICE  kept tabs  on immigrant rights groups’ social media activity, and in late 2018 and early 2019, CBP and HSI  used   information  gleaned from social media in compiling dossiers and putting out travel alerts on advocates, journalists, and lawyers — including U.S. citizens — whom the government suspected of helping migrants south of the U.S. border.

Muslim, Arab, Middle Eastern, and South Asian communities have often been particular targets of the U.S. government’s  discriminatory  travel and immigration screening practices, including social media screening. The State Department’s collection of social media identifiers on visa forms, for instance,  came out  of President Trump’s Muslim ban, while  earlier  social media monitoring and collection programs focused disproportionately on people from predominantly Muslim countries and Arabic speakers.

Is social media surveillance an effective way of getting information about potential threats?

Not particularly. Broad social media monitoring for threat detection purposes untethered from suspicion of wrongdoing generates reams of useless information, crowding out information on — and resources for — real public safety concerns.

Social media conversations are difficult to interpret because they are often highly context-specific and can be riddled with slang, jokes, memes, sarcasm, and references to popular culture; heated rhetoric is also common. Government officials and assessments have repeatedly recognized that this dynamic makes it difficult to distinguish a sliver of genuine threats from the millions of everyday communications that do not warrant law enforcement attention. As the former acting chief of DHS I&A  said , “actual intent to carry out violence can be difficult to discern from the angry, hyperbolic — and constitutionally protected — speech and information commonly found on social media.” Likewise, a 2021  internal review  of DHS’s Office of Intelligence & Analysis noted: “[s]earching for true threats of violence before they happen is a difficult task filled with ambiguity.” The review observed that personnel trying to anticipate future threats ended up collecting information on a “broad range of general threats that did not meet the threshold of intelligence collection” and provided I&A’s law enforcement and intelligence customers with “information of limited value,” including “memes, hyperbole, statements on political organizations and other protected First Amendment speech.” Similar  concerns  cropped up with the DHS’s pilot programs to use social media to vet refugees.

The result is a high volume of false alarms, distracting law enforcement from investigating and preparing for genuine threats: as the FBI bluntly  put it , for example, I&A’s reporting practices resulted in “crap” being sent through one of its threat notification systems.

What rules govern federal agencies’ use of social media?

Some agencies, like the FBI, DHS, State Department and  IRS , have released information on the rules governing their use of social media in certain contexts. Other agencies — such as the ATF, DEA, Postal Service, and Social Security Administration — have not made any information public; what is known about their use of social media has emerged from media coverage, some of which has attracted  congressional   scrutiny . Below we describe some of what is known about the rules governing the use of social media by the FBI, DHS, and State Department.

FBI:  The main document governing the FBI’s social media surveillance practices is its  Domestic Investigations and Operations Guide  (DIOG), last made public in redacted form in 2016. Under the DIOG, FBI agents may review publicly available social media information prior to initiating any form of inquiry. During the lowest-level investigative stage, called an assessment (which requires an “authorized purpose” such as stopping terrorism, but no factual basis), agents may also log public, real-time communications (such as public chat room conversations) and work with informants to gain access to private online spaces, though they may not record private communications in real-time.

Beginning with “preliminary investigations” (which require that there be “information or an allegation” of wrongdoing but not that it be credible), FBI agents may monitor and record private online communications in real-time using informants and may even use false social media identities with the approval of a supervisor. While conducting full investigations (which require a reasonable indication of criminal activity), FBI agents may use all of these methods and can also get probable cause warrants to conduct wiretapping, including to collect private social media  communications .

The DIOG does restrict the FBI from probing social media based  solely  on “an individual’s legal exercise of his or her First Amendment rights,” though such activity can be a substantial motivating factor. It also requires that the collection of online information about First Amendment-protected activity be connected to an “authorized investigative purpose” and be as minimally intrusive as reasonable under the circumstances, although it is not clear how adherence to these standards is evaluated.

DHS:  DHS policies can be pieced together using a combination of legally mandated disclosures — such as privacy impact assessments and data mining reports — and publicly available policy guidelines, though the amount of information available varies. In 2012, DHS published  a   policy  requiring that components collecting personally identifiable information from social media for “operational uses,” such as investigations (but not intelligence functions), implement basic guidelines and training for employees engaged in such uses and ensure compliance with relevant laws and privacy rules. Whether this policy has been holistically implemented for “operational uses” of social media across DHS remains unclear. However, the Brennan Center has obtained a number of templates describing how DHS components use social media, created pursuant to the 2012 policy, through the Freedom of Information Act.

In practice, DHS policies are generally permissive. The examples below illustrate the ways in which various parts of the Department use social media.

• ICE agents monitor social media for purposes ranging from situational awareness and criminal intelligence gathering to support for investigations. In addition to engaging private companies to monitor social media, ICE agents  may collect  public social media data whenever they determine it is “relevant for developing a viable case” and “supports the investigative process.”
• Parts of DHS, including the National Operations Center (NOC) (part of the Office of Operations Coordination and Planning ( OPS )), Federal Emergency Management Agency ( FEMA ), and Customs and Border Protection ( CBP ), use social media monitoring for situational awareness. The goal is generally not to “seek or collect” personally identifiable information. DHS may do so in “in extremis situations,” however, such as when serious harm to a person may be imminent or there is a “credible threat[] to [DHS] facilities or systems.” NOC’s situational awareness operations are not covered by the 2012 policy; other components carrying out situational awareness monitoring must create a but may receive an exception from the broader policy with the approval of DHS’s Chief Privacy Officer.
• DHS’s U.S. Citizenship and Immigration Services ( USCIS ) uses social media to verify the accuracy of materials provided by applicants for immigration benefits (such as applications for refugee status or to become a U.S. citizen) and to identify fraud and threats to public safety. USCIS says it only looks at publicly available information and that it will respect account holders’ privacy settings and refrain from direct dialogue with subjects, though staff may use fictitious accounts in certain cases, including when “overt research would compromise the integrity of an investigation.”
• DHS’s Office of Intelligence & Analysis (I&A), as a member of the Intelligence Community, is not covered by the 2012 policy. Instead it operates under a separate set of  guidelines  — pursuant to Executive Order 12,333, issued by the Secretary of Homeland Security and approved by the Attorney General — that govern its management of information collected about U.S. persons, including via social media. The office incorporates social media into the open-source intelligence reports it produces for federal, state, and local law enforcement; these reports provide threat warnings, investigative leads, and referrals. I&A personnel  may  collect and retain social media information on U.S. citizens and green card holders so long as they reasonably believe that doing so supports a national or departmental mission; these missions are broadly defined to include addressing homeland security concerns. And they may disseminate the information further if they believe it would help the recipient with “lawful intelligence, counterterrorism, law enforcement, or other homeland security-related functions.”

State Department.  The Department’s policies covering social media monitoring for visa vetting purposes are not publicly available. However,  public   disclosures  shed some light on the rules consular officers are supposed to follow when vetting visa applicants using social media. For example, consular officers are not supposed to interact with applicants on social media, request their passwords, or try to get around their privacy settings — and if they create an account to view social media information, they “must abide by the contractual rules of that service or platform provider,” such as Facebook’s real name policy. Further, information gleaned from social media must not be used to deny visas based on protected characteristics (i.e., race, religion, ethnicity, national origin, political views, gender or sexual orientation). It is supposed to be used only to confirm an applicant’s identity and visa eligibility under criteria set forth in U.S. law.

Are there constitutional limits on social media surveillance?

Yes. Social media monitoring may violate the First or Fourteenth Amendments. It is well established that public posts receive constitutional protection: as the investigations guide of the Federal Bureau of Investigation recognizes, “[o]nline information, even if publicly available, may still be protected by the First Amendment. Surveillance is clearly unconstitutional when a person is specifically  targeted  for the exercise of constitutional rights protected by the  First Amendment  (speech, expression, association, religious practice) or on the basis of a characteristic protected by the  Fourteenth Amendment  (including race, ethnicity, and religion). Social media monitoring may also violate the First Amendment when it burdens constitutionally protected activity and does not contribute to a legitimate government objective. Our  lawsuit  against the State Department and DHS ( Doc Society v. Blinken ), for instance, challenges the collection, retention, and dissemination of social media identifiers from millions of people — almost none of whom have engaged in any wrongdoing — because the government has not adequately justified the screening program and it imposes a substantial burden on speech for little demonstrated value. The White House office that reviews federal regulations noted the latter point — which a DHS Inspector General  report  and  internal reviews  have also underscored  — when it  rejected , in April 2021, DHS’s proposal to collect social media identifiers on travel and immigration forms.

Additionally, the  Fourth Amendment  protects people from “unreasonable searches and seizures” by the government, including searches of data in which people have a “reasonable expectation of privacy.” Judges have  generally   concluded  that content posted publicly online cannot be reasonably expected to be private, and that police therefore do not need a warrant to view or collect it. Courts are increasingly recognizing, however, that when the government can collect far more information — especially information revealing sensitive or intimate details — at a far lower cost than traditional surveillance, the Fourth Amendment  may protect  that data. The same is true of social media monitoring and the use of powerful social media monitoring tools, even if they are employed to review publicly available information.

Are there statutory limits on social media surveillance?

Yes. Most notably, the  Privacy Act  limits the collection, storage, and sharing of personally identifiable information about U.S. citizens and permanent residents (green card holders), including social media data. It also bars, under most circumstances, maintaining records that describe the exercise of a person’s First Amendment rights. However, the statute contains an exception for such records “within the scope of an authorized law enforcement activity.” Its coverage is limited to databases from which personal information can be retrieved by an individual identifier like a name, social security address, or phone number.

Additionally, federal agencies’ collection of social media handles must be authorized by law and, in some cases, be subject to public notice and comment and justified by a reasoned explanation that accounts for contrary evidence.  Doc Society v. Blinken , for example, alleges that the State Department’s collection of social media identifiers on visa forms violates the Administrative Procedure Act (APA) because it exceeds the Secretary of State’s statutory authority and did not consider that prior social media screening pilot programs had failed to demonstrate efficacy.

Is the government’s use of social media consistent with platform rules?

Not always. Companies do not bar government officials from making accounts and looking at what is happening on their platforms. However, after the ACLU  exposed  in 2016 that third-party social media monitoring companies were pitching their services to California law enforcement agencies as a way to monitor protestors against racial injustice,  Twitter ,  Facebook , and Instagram changed or clarified their rules to prohibit the use of their data for surveillance (though the actual  application  of those rules can be murky).

Additionally, Facebook has a  policy  requiring users identify themselves by their “real names,” with no exception for law enforcement. The FBI and other federal law enforcement agencies permit their agents to use false identities notwithstanding this rule, and there have been documented instances of other law enforcement departments  violating  this policy as well.

How do federal agencies share information collected from social media, and why is it a problem?

Federal agencies may share information they collect from social media across all levels of government and the private sector and will sometimes even disclose data to foreign governments (for instance,  identifiers  on travel and immigration forms). In particular, information is shared domestically with state and local law enforcement, including through fusion centers, which are post-9/11 surveillance and intelligence hubs that were intended to facilitate coordination among federal, state, and local law enforcement and private industry. Such unfettered data sharing magnifies the risks of abusive practices.

Part of the risk stems from the dissemination of data to actors with a documented history of discriminatory surveillance, such as fusion centers. A 2012 bipartisan Senate investigation  concluded  that fusion centers have “yielded little, if any, benefit to federal counterterrorism intelligence efforts,” instead producing reams of low-quality information while labeling Muslim Americans engaging in innocuous activities, such as voter registration, as potential threats. More recently,  fusion centers  have been  caught   monitoring  racial and social justice organizers and protests and  promoting  fake social media posts by right-wing provocateurs as credible intelligence regarding potential violence at anti-police brutality protests. Further, many police departments that get information from social media through fusion centers (or from federal agencies like the FBI and DHS directly) have a  history  of targeting and surveilling minority communities and activists, but lack basic policies that govern their use of social media. Finally, existing agreements  permit  the U.S. government to share social media data — collected from U.S. visa applicants, for example — with repressive foreign governments that are known to retaliate against online critics.

The broad dissemination of social media data amplifies some of the harms of social media monitoring by eliminating context and safeguards. Under some circumstances, a government official who initially reviews and collects information from social media may better understand — from witness interviews, notes of observations from the field, or other material obtained during an investigation, for example — its meaning and relevance than a downstream recipient lacking this background. And any safeguards the initial agency places upon its monitoring and collection — use and retention limitations, data security protocols, etc. — cannot be guaranteed after it disseminates what has been gathered. Once social media is disseminated, the originating agency has little control over how such information is used, how long it is kept, whether it could be misinterpreted, or how it might spur overreach.

Together, these dynamics amplify the harms to free expression and privacy that social media monitoring generates. A qualified and potentially unreliable assessment based on social media that a protest could turn violent or that a particular person poses a threat might easily turn into a justification for policing that protest aggressively or arresting the person, as illustrated by the examples above. Similarly, a person who has applied for a U.S. visa or been investigated by federal authorities, even if they are cleared, is likely to be wary of what they say on social media well into the future if they know that there is no endpoint to potential scrutiny or disclosure of their online activity. Formerly, one branch of DHS I&A had a  practice  of redacting publicly available U.S. person information contained in open-source intelligence reports disseminated to partners because of the “risk of civil rights and liberties issues.” This practice was an apparent justification for removing pre-publication oversight to identify such issues, which implies that DHS recognized that information identifying a person could be used to target them without a legitimate law enforcement reason.

What role do private companies play, and what is the harm in using them?

Both  the   FBI  and  DHS  have reportedly hired private firms to help conduct social media surveillance, including to help identify threats online. This raises concerns around transparency and accountability as well as effectiveness.

Transparency and accountability:  Outsourcing surveillance to private industry obscures how monitoring is being carried out; limited information is available about relationships between the federal government and social media surveillance contractors, and the contractors, unlike the government, are not subject to freedom of information laws. Outsourcing also weakens safeguards because private vendors may not be subject to the same legal or institutional constraints as public agencies.

Efficacy:  The most ambitious tools use artificial intelligence with the goal of making judgments about which threats, calls for violence, or individuals pose the highest risk. But doing so reliably is beyond the capacity of both humans and existing technology, as more than 50 technologists  wrote  in opposing an ICE proposal aimed at predicting whether a given person would commit terrorism or crime. The more rudimentary of these tools look for specific words and then flag posts containing those words. Such flags are overinclusive, and garden-variety content will regularly be  elevated . Consider how the word “extremism,” for instance, could appear in a range of news articles, be  used  in reference to a friend’s strict dietary standards, or arise in connection with discussion about U.S. politics. Even the best Natural Language Processing tools, which attempt to ascertain the meaning of text, are prone to  error , and fare particularly  poorly  on speakers of non-standard English, who may more frequently be from minority communities, as well as speakers of languages other than English. Similar  concerns  apply to mechanisms used to flag images and videos, which generally lack the context necessary to differentiate a scenario in which an image is used for reporting or commentary from one where it is used by a group or person to incite violence.

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• Open access
• Published: 22 July 2022

Nursing students’ use of social media in their learning: a case study of a Canadian School of Nursing

• Catherine M. Giroux   ORCID: orcid.org/0000-0003-1352-8501 1 &
• Katherine A. Moreau   ORCID: orcid.org/0000-0002-5955-1689 2  

BMC Nursing volume  21 , Article number:  195 ( 2022 ) Cite this article

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Social media has diverse applications for nursing education. Current literature focuses on how nursing faculty use social media in their courses and teaching; less is known about how and why nursing students use social media in support of their learning.

The purpose of this study was to explore how nursing students use social media in their learning formally and informally.

This exploratory qualitative case study of a Canadian School of Nursing reports on the findings of interviews ( n  = 9) with nursing students to explore how they use social media in their learning. Data were analyzed using a combined deductive and inductive coding approach, using three cycles of coding to facilitate category identification.

Results and conclusions

The findings demonstrate that participants use social media for formal and informal learning and specifically, as a third space to support their learning outside of formal institutional structures. Social media plays a role in the learning activities of nursing students studying both face-to-face and by distance. Accordingly, social media use has implications for learning theory and course design, particularly regarding creating space for student learning communities.

Peer Review reports

Social media are online platforms that allow users to connect with other users, curate lists of connections, and interact with each other within the same online platform [ 1 ]. They have applications for both formal and informal learning in health professions education (HPE). Formal learning refers to planned educational experiences, such as courses or assignments [ 2 ] whereas informal learning refers to what is learned through extracurricular activities [ 3 , 4 ]. With social media, formal learning may include such activities as using YouTube videos in class, while informal learning may involve students scrolling through Twitter and finding relevant learning content on their leisure time. Within the HPE literature, social media have been shown to facilitate electronic communication, networking, and real-time collaboration [ 5 , 6 ]. They have also assumed key educational and communicative roles during the COVID-19 pandemic [ 7 , 8 , 9 ]. Furthermore, they continue to allow individuals to engage in independent, informal learning on their own terms and in places of formal education, work, or broader social circles [ 10 ]. Several studies demonstrated how social media can be used to facilitate clinical and professional performance tasks, question-and-answer sessions, and the exploration of complex topics collaboratively; social media can also provide professional learning opportunities and facilitate networking with international practitioners [ 11 , 12 , 13 , 14 ]. Moreover, instructors have used Twitter to provide students with formative feedback in assessment, stimulate reflection and sharing, share daily learning goals, hold journal clubs, notify students of recent topical publications, and orient learners to clinical sites and educational rotations [ 15 , 16 , 17 ]. The literature suggests that the connections that students make using social media can translate to opportunities for mentorship and scholarship [ 18 ]. Moreover, social media may also engage geographically dispersed individuals to create or share content, collaborate in groups, and ultimately form a virtual community [ 19 , 20 ].

Within the nursing education literature, social media is well described as a tool selected by faculty for diverse formal teaching and learning purposes. For instance, several studies described using blogging to facilitate reflections as a teaching strategy for topics such as cultural competence, empathy, the therapeutic relationship, transitions to practice, and self-care [ 21 , 22 , 23 , 24 , 25 ]. The feedback system of the blogging interface provided students with opportunities to practice their reflection and problem-solving skills [ 26 , 27 ]. Some studies used social media to simulate patient encounters or transition experiences for nurses [ 25 , 28 , 29 ]. For example, Thomas et al. used a blog to simulate a new nurse who had just transitioned to practice; the blog was written from the new nurse’s perspective to help final year nursing students consider issues of delegating and supervising, adapting to change, risk and quality management, and legal and ethical issues as they prepared to transition to practice [ 25 ]. Students had to read the blog and post responses. Other studies focused on using Facebook or YouTube as collaborative and interactive tools to help nursing students prepare for examinations like the National Council Licensure Examination (NCLEX) [ 30 , 31 , 32 ]. Still, issues of professionalism arose in the nursing education literature, with some studies noting concerns about students’ online behaviour and potential implications for their reputations and licensure [ 5 , 33 ]. A 2021 narrative review found that learning about digital professionalism concepts as they relate to social media influenced how students behaved online [ 34 ]. Despite these potential professionalism implications, social media appears to be an effective tool to support formal learning in nursing education. A 2018 systematic review explored the effectiveness of using social media in nursing and midwifery education [ 35 ]. The authors found that the collaborative, interactive, and semi-synchronous nature of social media platforms may support knowledge and skill acquisition in nursing students.

Much of the extant undergraduate nursing education literature explores how social media is used in formal learning, specifically from the perspectives of the faculty who select the platforms to suit specific assignments or learning goals. Studies that focus on undergraduate students’ use of social media tended to explore specific platforms used and data analytics (i.e., hashtags used, number of views or shares). Less is known about how and why undergraduate nursing students themselves select social media platforms as an adjunct to their formal and informal learning activities. Thus, this exploratory qualitative case study aimed to address how and why undergraduate nursing students use social media to support their learning.

Theoretical considerations

Social learning theories like social constructivism are appropriate for framing studies involving social media because they view learning as an active and collaborative process [ 36 , 37 , 38 ]. Social constructivism is based on three assumptions: (1) meanings are constructed by humans as they engage with the world they are interpreting; (2) humans engage with their world and make sense of it based on their historical and social perspectives; and (3) the basic generation of meaning is social, arising from the interaction with a human community [ 36 ]. Social constructivism claims knowledge is acquired when subjective meanings are created in interaction with others, drawing on material from previous experiences to guide learning [ 36 , 37 , 38 ]. This study was informed by social constructivism, which influenced our research questions, data collection instruments, and approaches to data analysis.

Research design

The objective of this study was to explore how students at one Canadian School of Nursing used social media to support their learning. We addressed this objective through an exploratory qualitative single case study. Yin [ 39 ] describes a case study as an empirical inquiry that investigates a contemporary phenomenon in depth within its real-world context even when the boundaries between the context and phenomenon may not be evident. Case studies comprise an all-encompassing method, which influences the logic of design, data collection techniques, and approaches to data analyses. Case study research is particularly useful for answering how and why questions; single case studies are appropriate for cases that are critical, unusual, revelatory, and longitudinal [ 39 ]. Our study site represented a critical case since the variety of program delivery methods and modalities were critically aligned with social constructivism. The study site also represented an unusual case, with four distinct program options – including a distance program – for students to achieve a Bachelor of Science in Nursing (BScN) degree. This was a unique program in Canada at the time of the study. The study site did not have any social media policies published to their public-facing website during the time of the study, nor did they have any public-facing references to using social media formally in their programs published on their website.

Case study site and participants

This study took place at a small, relatively northern, Canadian university with a student population of approximately 5,090 students [ 40 ]. The School of Nursing, which includes 1191 students, offers four distinct, English-language, options for students to complete their BScN degree. These options include: 1) a standard four-year direct-entry nursing program; 2) an onsite Registered Practical Nurse (RPN) to BScN bridging program for students who previously obtained an RPN diploma and who are looking to subsequently obtain their BScN degree; 3) a part-time blended learning RPN to BScN bridging program for students currently working as RPNs who are looking to obtain their BScN; and 4) a second entry accelerated program for students who previously obtained an undergraduate degree. Only two of the nursing programs occur at the case study site itself. The second entry program is held in a large city to the south of the case study site. Additionally, students who partake in the RPN to BScN bridging program through blended learning live geographically dispersed throughout the province in which the case study site is located. Given the different program options, the participants in this study consisted of a mixture of face-to-face students and distance students. Additionally, due to the nature of the program options, some participants had pursued their nursing program as their first degree while others were already working as RPNs and had returned to school to obtain their BScN degree.

Participant recruitment and data collection

Participants were purposively recruited from a previous study, which consisted of a digital artifact collection that explored what content nursing students shared to their Twitter, Facebook, and Instagram accounts related to learning [ 41 ]. The twenty-four nursing students who participated in our previous study were contacted by email and invited to participate in this qualitative case study exploring how and why nursing students use social media to support their learning. These students were identified as potential participants because they had confirmed using social media for learning and thus, would be information-rich interviewees for the present study. All potential participants were provided with a Participant Information Letter and Informed Consent form. The data for this study were collected using semi-structured interviews. All interviews were conducted virtually via Zoom in the Fall of 2019, using a semi-structured interview guide that had been developed based on the research questions, our theoretical framework, and the literature (refer to Additional file 1 : Appendix). Prior to using the interview guide, it was piloted with two registered nurses. This pilot involved conducting two mock interviews and debriefing the interview guide with the participants to discuss the feasibility and appropriateness of the interview questions. The average interview length was 32 min, with the shortest being 21 min and the longest being 44 min long. We piloted the interview guide with two registered nurses prior to commencing the study. Each interview was audio-recorded and transcribed verbatim. Interview participation was incentivized with a $20 gift card to a local coffee chain.

Data analysis

We took a combined deductive and inductive approach to coding and analyzing the interview transcripts. We sought to achieve theoretical sufficiency, which is the stage at which codes and categories manage new data without requiring further modification [ 42 ]. To do this, we conducted three cycles of coding in MAXQDA (v.18.2). In the first cycle, a preliminary codebook − which was informed by our research question, theoretical framework, and the literature − facilitated descriptive and process coding [ 43 ]. In the second cycle of coding, we each independently inductively coded the data using both process coding and in vivo coding (i.e., using the participants’ own words) and compared and discussed our coding. In the third cycle of coding, we grouped these summaries into categories, themes, or constructs [ 43 ]. A combination of matrices and networks visually displayed the data and facilitated category identification [ 43 , 44 ].

Reflexivity and trustworthiness

Neither author is a Registered Nurse nor is affiliated with the case study site. Both authors have expertise in conducting educational research within the health professions and were involved in the study conceptualization, data collection, and analysis. We also took steps to ensure that our analyses were credible, dependable, confirmable, and transferable [ 45 , 46 ]. To establish credibility, we engaged in member-checking, wherein we provided the participants a copy of their interview transcripts so that they could ensure that their statements were accurately represented during transcription [ 45 , 47 ]. We also engaged in peer debriefing. In terms of dependability, each of us inductively coded the data, compared our coding, and discussed and resolved any inconsistencies. In addition, we used audit trails as a strategy to ensure confirmability. These audit trails documented each of our decisions made during the research process and would allow an independent auditor to follow our steps and decisions to establish the same conclusions about the data. Lastly, through purposeful sampling and information-rich interviewees, we were able to obtain thick descriptions of how and why the students use social media to support their learning. We also included detailed descriptions of our research processes. This level of description allows others to judge the contextual similarity and transferability of our study findings.

Ethical considerations

The interviews received formal institutional ethical approval (S-08–18-921) and approval from the study site (101916) in August 2019. We reviewed the informed consent form with each participant prior to commencing the interview and addressed any questions that they had. All participants verbally consented to participate in an interview and participants’ consent was recorded using Zoom video conference software, in accordance with our research ethics board approval.

Nine nursing students ( n  = 9) participated in the individual interviews. All participants were female and ranged in age from 18 to 49. Five participants attended classes online in a blended program format that occurred by distance and four participants attended classes face-to-face. The findings demonstrate that participants used social media in numerous ways for both formal and informal learning purposes. Table 1 provides a thematic overview of how the nursing student participants use social media in support of their learning.

Formal learning

Participants reported using social media for a variety of purposes pertaining to formal learning. Table 2 provides exemplary participant quotes outlining their experiences using social media for formal learning purposes.

Sharing and clarifying course content

Several participants reported using social media to share content related to their courses and to clarify course content. Participant 7 explained how “when it comes to having, like, a large quantity of information, I think Facebook’s a better platform for that. Um, you’re able to share different links, you’re able to share pictures, videos, news articles, almost anything, it seems now”. Two participants (Participants 05 and 07) shared contrasting experiences with using social media formally in their distance classes to clarify course concepts. In this instance, a professor had shared YouTube videos in the course. While Participant 7 appreciated the inclusion of videos, Participant 5 found this approach to be lazy, especially since the professor did not create the videos but rather included videos that, according to Participant 5, students would likely search for on their own to assist their learning.

Supplementing university services

Eight participants indicated that Facebook was a good platform to supplement or highlight existing university services. Participant 5 explained how, as a distance student, they used Facebook to learn about the services available to students, like the university’s tutoring service, which Participant 5 found helpful for statistics. Participant 6 described how they used Facebook specifically for sharing course resources, since that platform might be easier at times than the typical learning management system.

Assignments and exams

The participants described using social media as a mechanism to complete their course assignments and to study for course exams and the National Council Licensure Examination (NCLEX). Social media appeared to be involved in the process of completing assignments; it also appeared to be the product of some assignments. Participant 5 described how “any group projects that we have to do would, which in an online program seems a little silly to me to do group projects but, um, we’d have to find a way to collaborate and it was often over Facebook or that sort of thing”. Participant 1 described creating a social media campaign for their community health class to help parents access vision care for their school-age children. Participant 3 shared how they found posts about how to pass the NCLEX the first time shared to social media and Participant 2 explained how they use social media to review for their course exams by dividing course content up amongst a small group of students and sharing review notes and summaries online. Participant 2 also described using social media platforms like Reddit to understand the patient experience based on what patients choose to share to these sites.

Informal learning

Participants indicated that they used social media for diverse informal learning purposes. Table 3 provides an overview of participants’ experiences using social media for informal learning.

Creating community

By far, students shared the value of social media for connecting with peers and the nursing community most frequently. Four participants spoke about how social media promotes connection between distance students. Participant 3 shared how social media “gives you that camaraderie that you’re missing in a classroom environment”. Four out of the five students who identified as an online student cited Facebook groups as being an important mechanism for connecting with their classmates who were spread throughout the province. One participant explained how “there is a group online, uh, [School Name] distance ed students so I use that quite a bit, um, just to get information on classes, um, what to expect from different professors, etc.” Five participants shared how social media helped them combat isolation in their learning. Participant 2 emphasized the importance of social media for connecting distance students, which was important since they did not have the same opportunities to meet their classmates face-to-face. Participant 1 described how participating in Facebook groups helped enhance both the academic and social aspects of their face-to-face learning experience. Participant 4 explained how “we find it’s been really useful, or even like finding little things, like finding rides to clinical and stuff like that. Like obviously not all of us can afford vehicles and stuff like that so just by helping each other out”. In fact, every participant who identified as a face-to-face student ( n  = 4) spoke about the importance of Facebook groups to their learning experience since they contributed to building community and sharing resources.

Similarly, six participants shared how social media connected them with the broader nursing community, outside of their programs and university. Participant 6 described how social media could connect people across the country with experts in the field and the resources they have created. Participant 9 explained how social media could be used to “take my learning outside of the avenues that can be addressed and presented within a program or any program, really. So, it allows you to kind of step outside of that, see what’s happening with other people, how they’re learning…” Participant 1 described how social media allows them to connect with the nursing community on both social and academic levels through sharing memes and experiences on platforms like Instagram and Facebook. Participant 3 shared how social media “probably gives a good, like, um, a good alternative perspective on things, other than the teacher’s”.

‘Behind the scenes’ knowledge sharing

While the participants often spoke about content that was publicly available to them on social media, they also shared how they used social media for informal learning purposes in private or ‘behind the scenes’ ways. Five nursing students reported using social media to buy, sell, and share PDF versions of textbooks. Participant 5 shared how “people share PDFs of textbooks and all that sort of stuff, so it’s definitely saved me several hundred dollars”. Two participants expressed how they prefer social media to textbooks. Participant 9 described how their professors are “not the biggest towards textbooks because they said that the second they are printed they are out of date because of how fast information is changing within healthcare”. In this sense, Participant 9 found social media to be a helpful way to stay up to date with information that textbooks did not provide.

Similarly, three participants described using social media to discuss which professors were the best for each class. Participant 2 explained how “we often talk about which professors are the best for specific courses and so those classes tend to fill up really fast”. Participant 5 described how they use social media to ask questions about the university, share their perceptions of certain professors, and discuss which classes should or should not be taken at the same time. While eight of the nine interview participants actively participated in social media groups, three participants shared that the absence of faculty members in the social media groups could be problematic. Participant 2 suggested using more of the collaborative tools available on the university’s learning management system to eliminate some of the need for the social media groups and better include the faculty members. Participant 5 also found the absence of faculty members in the social media groups to be a problem and recommended involving faculty members in the private groups to correct misinformation and answer questions.

Scaffolding knowledge

In addition to sharing resources, three students indicated that the Facebook groups were essential for giving and receiving support throughout their nursing programs. Similarly, five nursing students shared how they use social media to review their clinical skills. Three participants used social media to review IV insertion. Participant 7 described how “I use Instagram, I follow someone, she, her, her tag is IV Queen or something like that, but she gives a lot of intravenous tips on how to insert IVs and how to care for them”. Participant 3 also described using YouTube videos to review IV compatibility. Participant 1 shared how they used YouTube to practice for their IV therapy lab. Participant 1 also described how “we have used some YouTube videos and tutorials and stuff in our labs where we’re able to view, like, for example just last week we were learning about central lines, um, so we looked at a video about how to do the dressing change for a central line”. Participant 1 also described how they use YouTube to learn about skills like ambulating patients prior to starting their surgical rotation so that they would understand what they were about to do on the rotation.

Why use social media

The study participants presented several reasons to use social media in support of their formal and informal learning activities; similarly, they also presented several reasons to be cautious of using social media for these purposes. Table 4 presents an overview of exemplary participant quotations presented thematically.

Credibility and relevance of sources

Seven participants discussed the credibility and relevance of the sources they found on social media. Participant 7 indicated that they find their friends and followers on social media do not tend to share a lot of content that “I don’t consider real, like the fake news, but it’s a lot of more credible sources, like major journal articles and stuff like that”. Participant 4 expressed that students are taking a risk in depending on social media rather than on their books and their notes. Other students, like Participant 6, emphasized the importance of developing critical thinking skills and being able to filter social media posts so that they could appropriately determine which sources were accurate or credible. Participant 8 indicated that relying on social media links provided by course professors was helpful since “you know if the instructors are posting those videos, then you know that they’re credible sources.”

Professors and professionalism

All nine nursing students shared how their professors, programs, and the importance of professionalism influenced their use of social media. Four participants shared that, perhaps with the exception of YouTube videos, their professors did not use social media in their teaching and discouraged its use by nursing students. Participant 6 explained that “social media is kind of shunned a lot in nursing because of that whole idea of don’t post anything, don’t share your clinical experiences and don’t, you know, breach privacy.” In some instances, participants reported that their professors did not use social media in their teaching but encouraged students to use it to complete course assignments, like learning portfolios. Participant 4 shared that “[the professors] really like the idea of us working together on things and utilizing each other to keep on track”, especially as it related to support during clinical placements.” Other participants described their professors incorporating podcasts, videos, and Reddit into their courses, which encouraged their use of social media for learning. Still, several participants expressed concerns related to professionalism on social media. Participant 3 explained how “I definitely avoid posting about like, things that involve substance use. I feel like there’s added pressure on people in certain, in various professions like healthcare and police that you should avoid because you’re supposed to uphold a certain image of the profession.”

Convenience and accessibility

Several participants discussed the convenience of social media. Two participants shared how it was easier for communication purposes than other methods (i.e., emails, calls, texts). Other participants described how social media provided a central repository for resources that could be easily accessed by classmates. However, Participants 3 and 5 highlighted some challenges to accessibility because of using social media for learning, notably poor internet connection and lack of transcriptions or alternative formats.

Engagement and distraction

Four participants shared how they found social media to be an engaging platform for learning in their nursing education. Participant 4 explained how social media helps highlight major class concepts in a variety of formats, which can be helpful for different learners. Several participants spoke about growing up with social media and how their previous experiences motivated them to use it as a tool to support their nursing education. Participant 6 explained how “I kind of grew up with technology and grew up with social media that I just know how to use it and know how to access it and don’t have a problem filtering out what I don’t need.” Despite how participants felt about social media’s potential for engagement, they also found it potentially distracting. This was a common theme amongst both face-to-face and distance students. Participant 2 described ending up in a “Facebook vortex, where I end up being on it for 2 h, not necessarily on that [program specific] group.”

The nursing student participants described multiple ways of using social media to support their learning. None of the students in this study described using social media for the same creative formal experiences as those published by Thomas et al. [ 25 ] wherein a course instructor developed a simulated student on Facebook for nursing students to interact with online. However, a couple of students outlined their experiences being required to use sites like Reddit to learn about the patient experience. Additionally, some participants described how they used social media to develop patient-oriented health advocacy campaigns for healthcare organizations, effectively demonstrating how social media is being used in their formal nursing education. The ways in which the nursing students use social media to support their formal learning demonstrate social media’s collaborative capacity for knowledge and information exchange for both on-campus and distance students [ 6 , 48 , 49 ]. The study participants used social media creatively to support their formal education; for instance, participants referenced program-specific Facebook groups where they could collectively decide on questions that they needed to ask their professors in class. This finding is consistent with that of Junco et al. [ 50 ], where they found social media to be a low-stress method for students to ask questions of their peers and educators.

Informally, participants indicated using social media to refresh their clinical skills before applying them in lab settings or during clinical rotations. While the findings of this study do not directly touch on the use of social media at the point-of-care, studies like that conducted by Hay et al. [ 51 ] demonstrate social media’s potential utility for enhanced clinical learning and patient safety. In this study, two participants described how they use social media, specifically YouTube videos, to help with patient education at the bedside. Moreover, the participants indicated that they took a cautious approach to using social media in their formal and informal learning out of concern for professionalism implications. Several students indicated that they had been warned about the repercussions of unprofessional online behaviour and had adjusted their behaviour accordingly. This finding is similar to that of a previous conducted narrative review by O’Connor et al. [ 34 ] that found that students were likely to change what content they shared using social media after learning about issues of professionalism.

Importantly, the participants in this study appeared to use social media as a third space. Aaen and Dalsgaard [ 52 ] describe the ‘third space’ as being one that emerges in boundaries or overlaps across spheres; they explain that third spaces emerge from a need for discourses that are unavailable or cannot be filled in existing settings. Participants described creating their own Facebook groups for their classes, cohorts, study groups, clinical groups, and programs. The students explained that faculty members were not present in their Facebook groups, although they did sometimes encourage students to join the groups to stay up to date on information. The participants shared that they used the groups to fill gaps in their education. Others described using the Facebook groups to create a sense of community they felt was missing in their distance learning. In fact, this study found that nursing students use social media in their education in several ways that are often hidden or ‘behind the scenes’. Aaen and Dalsgaard [ 52 ] found that Facebook formed a ‘third space’ that combined elements of academic, personal, and social communication that does not typically take place within conventional university structures or spaces. The findings of this study are similar in the sense that the nursing student participants used social media as a mechanism to collaborate, communicate, teach, and learn when traditional university avenues were unavailable to them.

This study has implications for learning theory in connected teaching and learning. Learning theories – and thus, approaches to teaching – have moved from behaviourist to constructivist in the age of technology [ 53 ]. Indeed, social learning theories like connectivism [ 54 ], Communities of Practice [ 55 ], and social constructivism [ 36 ] can reflect the realities of connected teaching and learning because they focus on collective learning and knowing in both physical and digital spaces. In the present study, social constructivism, specifically Vygotsky’s Zone of Proximal Development, is evident in the participants’ use of social media for formal and informal learning purposes. Vygotsky [ 56 ] defines the Zone of Proximal Development as “the distance between the actual development level as determined by independent problem solving and the level of potential development as determined through problem solving under adult guidance or in collaboration with capable peers” (p. 86). The participants in this study described using online social media groups to share information about course requirements, assignment information, and exam tips. Social media also appeared to be a method for students to consolidate, share, and engage in their learning as part of a larger social process. Several participants described experiences of scaffolding learning for their peers either within their own cohort or in cohorts behind them using social media groups. Scaffolding is a key component of Vygotsky’s Zone of Proximal Development and has applications for online course design; technical scaffolding allows learners to experience just-in-time instruction and be provided with resources to solve problems and generate new learning and understanding collaboratively online [ 57 ]. Thus, the online learning environment should provide learners with the resources, tools, and supports they need to build their own knowledge; scaffolding fades as learners develop their own knowledge and expertise [ 53 ].

Implications for nursing education policy and practice

This study demonstrates that nursing students are using social media in their educational practices both formally and informally. This use of social media has implications for teaching and learning in nursing education. Faculty members must consider the purposes for which nursing students are using social media, especially informally. One finding of this study suggested that nursing students turned to social media to fill perceived gaps – both academic and social – in their learning experience. If faculty members and schools of nursing are aware that social media is being used by nursing students for formal and informal teaching and learning purposes, it can be leveraged to achieve specific competencies and learning objectives. Based on this study, we have highlighted recommendations for nursing education policy and practice.

At the policy level, professional and appropriate social media communication could be included as an educational competency in nursing education programs, if not already stated in guiding curriculum frameworks. The purpose of this recommendation is not to discourage social media use but rather to develop competent online communicators who are equipped to use social media for teaching, learning, advocacy, and knowledge translation purposes. At the institution level, increased training for both faculty members and students on digital literacies, identifying credible online sources, and managing misinformation could help ensure faculty and students feel equipped to use digital tools like social media effectively in their teaching and learning. Finally, at the course level, some participants valued using social media to extend their learning while others were more reluctant to use it; thus, approaching the use of social media with flexibility and allowing for choice is essential. Providing optional opportunities to extend learning may help encourage participation on social media and help students discover how social media platforms can be used as learning tools informally within the nursing profession.

Limitations and future directions

This exploratory qualitative case study included individual semi-structured interviews with nursing students from one Canadian School of Nursing. Despite incentivizing interview participation, we were only able to recruit 9 of the 24 possible participants. It is also probable that those who participated were more interested in social media than those who did not participate. The interviews consisted of self-reported data from the perspectives of the participants. Although participants spoke about how their professors used social media in their courses, the professors’ perspectives were not included in this study, leaving a potential imbalance and area for future research. Moreover, our small qualitative sample did not allow for a stratified analysis based on the program delivery method. This type of analysis would be interesting to conduct with a larger, quantitative dataset. Lastly, while the interview guide included questions about the nursing student participants’ experiences using social media, it did not include questions about their cultural backgrounds. In future, it would be interesting to explore how students’ culture backgrounds influence how and why they use of social media.

Conclusions

The nursing students in this study described and demonstrated using social media to support their formal and informal learning. The participants also used social media as a third space, one that is separate from the traditional confines of the university. Within this space, participants merged their personal and academic discussions to collaborate, share resources, mentor one another, and connect with nursing experts and professional institutions. This use of social media has implications for teaching and learning in nursing education, especially regarding learning theory, scaffolding, and online course design.

Availability of data and materials

Due to the qualitative case study nature of this research, the data generated and analyzed during the current study are not publicly available to maintain the anonymity of the study participants. Data are available from the corresponding author on reasonable request.

Boyd dm, Ellison NB. Social network sites: definition, history, and scholarship. J Comput Mediat Commun. 2007;13(1):210–30.

Article   Google Scholar  

Thomas P, Kern D, Hughes M, Chen B. Curriculum development for medical education: a six-step approach. 3rd ed. Baltimore, MD: The Johns Hopkins University Press; 2016.

Google Scholar  

Edmunds A, Nickel J, Badley K. Curriculum: designing meaningful learning experiences. In: Educational foundations in Canada. Don Mills, ON: Oxford University Press; 2015. p. 69–117.

Gofton W, Regehr G. What we don’t know we are teaching: unveiling the hidden curriculum. Clin Orthop Relat Res. 2006;449:20–7.

Article   PubMed   Google Scholar  

Duke V, Anstey A, Carter S, Gosse N, Hutchens K, Marsh J. Social media in nurse education: utilization and E-professionalism. Nurse Educ Today. 2017;57:8–13.

Ventola C. Social media and healthcare professionals: benefits, risks, and best practices. Pharmacy and Therapeutics. 2014;39(7):491–9.

PubMed   PubMed Central   Google Scholar  

Lu D, Ruan B, Lee M, Yilmaz Y, Chan TM. Good practices in harnessing social media for scholarly discourse, knowledge translation, and education. Perspect Med Educ. 2021;10(1):23–32.

Gottlieb M, Dyer S. Information and Disinformation: Social Media in the COVID-19 Crisis. Acad Emerg Med. 2020;27(7):640–1.

Article   PubMed   PubMed Central   Google Scholar  

Merchant R, Lurie N. Social media and emergency preparedness in response to novel Coronavirus. JAMA. 2020;323(20):2011–2.

Article   CAS   PubMed   Google Scholar  

Bell F. Connectivism: Its place in theory-informed research and innovation in technology enabled learning. Int Rev Res Open Dist Learn. 2011;12(3):98–118.

Cohn RJ, Plack MM. A cloud with a silver lining: helping students learn about professionalism. Teach Learn Med. 2017;29(3):304–12.

Craig J, Wong R. Student perceptions of the use and value of wiki technology for the creation and dissemination of an orthopedic physical therapy assignment. Journal of Physical Therapy Education. 2013;27(1):70–6.

Erardi L, Hartmann K. Blogs, wikis, and podcasts: Broadening our connections for communication, collaboration, and continuing education. OT Pract. 2008;13(9):CE1–8.

Guckian J, Utukuri M, Asif A, Burton O, OAdeyoju J, Oumeziane A, et al. Social media in undergraduate medical education: a systematic review. Med Educ. 2021;55(11):1227–41.

Forgie SE, Duff JP, Ross S. Twelve tips for using twitter as a learning tool in medical education. Med Teach. 2013;35(1):8–14.

Kind T, Patel P, Lie D, Chretien K. Twelve tips for using social media as a medical educator. Med Teach. 2014;36(4):284–90.

Minter D, Geha R, Manesh R, et al. The future comes early for medical educators. J Gen Intern Med. 2021;36:1400–3.

Pereira I, Cunningham A, Moreau K, Sherbino J, Jalali A. Thou shalt not tweet unprofessionally: an appreciative inquiry into the professional use of social media. Postgrad Med J. 2015;91(1080):561–4.

Comp G, Dyer S, Gottlieb M. Is TikTok the next social media frontier for medicine? AEM Educ Train. 2021;5(3):1–4.

Sherbino J. The social media summit in health professions education. Postgrad Med J. 2015;91(1080):542–3.

Arbour M, Kaspar RW, Teall AM. strategies to promote cultural competence in distance education. J Transcult Nurs. 2015;26(4):436–40.

Chu SKW, Chan CKK, Tiwari AFY. Using blogs to support learning during internship. Comput Educ. 2012;58(3):989–1000.

Garrity M, Jones K, VanderZwan K, de la Rocha A, Epstein I. Integrative review of blogging: implications for nursing education. J Nurs Educ. 2014;53(7):395–401.

Reed SJ, Edmunds D. Use of a blog in an undergraduate nursing leadership course. Nurse Educ Pract. 2015;15(6):537–42.

Thomas CM, Bertram E, Allen R. Preparing for transition to professional practice: creating a simulated blog and reflective journaling activity. Clin Simul Nurs. 2012;8(3):e87–95.

Chu LF, Erlendson MJ, Sun JS, Clemenson AM, Martin P, Eng RL. Information technology and its role in anaesthesia training and continuing medical education. Best Pract Res Clin Anaesthesiol. 2012;26(1):33–53.

Reed KS. Bags and blogs: creating an ostomy experience for nursing students. Rehabil Nurs. 2012;37(2):62–5.

Gunberg Ross J. Integration of social media into nursing education. In: Pennsylvania Nurse. 2015. p. 4–10.

Ross JG, Beckmann B, Goumas C. baccalaureate nursing students’ perceptions of the use of a facebook case study as a teaching strategy. Nurs Educ Perspect. 2019;40(3):174–5.

Morales K. Active learning strategies to enhance nursing students’ knowledge of pharmacology. Nurs Educ Perspect. 2017;38(2):100–2.

Tower M, Latimer S, Hewitt J. Social networking as a learning tool: nursing students’ perception of efficacy. Nurse Educ Today. 2014;34(6):1012–7.

May O, Wedgeworth M, Bigham A. Technology in nursing education: youtube as a teaching strategy. J Pediatr Nurs. 2013;28(4):408–10.

Basevi R, Reid D. Ethical guidelines and the use of social media and text messaging in healthcare: A review of the literature. N Z J Physiother. 2014:68–80.

O’Connor S, Zhang M, Honey M, Lee JJ. Digital professionalism on social media: a narrative review of the medical, nursing, and allied health education literature. Int J Med Inf. 2021;153: 104514.

O’Connor S, Jolliffe S, Stanmore E, Renwick L, Booth R. Social media in nursing and midwifery education: a mixed study systematic review. J Adv Nurs. 2018;74(10):2273–89.

Creswell J. Research design: quantitative, qualitative, and mixed methods approaches. Thousand Oaks, CA: Sage Publications, Ltd.; 2003.

Dewey J. Democracy and education: An introduction to the philosophy of education. USA: Feather Trail Press; 1916.

Reich K. Constructivism: diversity of approaches and connections with pragmatism. In: Hickman L, Neubert S, Reich K, editors. John Dewey: between pragmatism and constructivism. New York, NY: Fordham University Press; 2009. p. 39–66.

Chapter   Google Scholar  

Yin R. Case study research: Design and methods. Thousand Oaks, CA: SAGE; 2014.

Universities Canada. 2019 full-time and part-time fall enrolment at Canadian universities. 2019. Available from:. https://www.univcan.ca/universities/facts-and-stats/enrolment-by-university/ .

Giroux CM, Moreau KA. A Qualitative Exploration of the Teaching- and Learning-Related Content Nursing Students Share to Social Media. Can J Nurs Res. 2021:8445621211053113.

Varpio L, Ajjawi R, Monrouxe LV, O’Brien BC, Rees CE. Shedding the cobra effect: problematising thematic emergence, triangulation, saturation and member checking. Med Educ. 2017;51(1):40–50.

Miles M, Huberman A, Saldana J. Qualitative data analysis: a methods sourcebook. Thousand Oaks, CA: SAGE; 2014.

Creswell J, Plano Clark V. Designing and conducting mixes methods research. 3rd ed. Washington, DC: SAGE; 2018.

Guba E. Criteria for assessing the trustworthiness of naturalistic inquiries. Education and Communicational Technology Journal. 1981;29(2):75–91.

Lincoln Y, Guba E. Naturalistic inquiry. Newbury Park, CA: SAGE; 1985.

Book   Google Scholar  

Creswell J, Plano Clark V. Designing and conducting mixed methods research. Thousand Oaks, CA: SAGE; 2011.

D’Souza K, Henningham L, Zou R, Huang J, O’Sullivan E, Last J, et al. Attitudes of health professional educators toward the use of social media as a teaching tool: global cross-sectional study. J Med Internet Res. 2017;3(2).

Giordano C, Giordano C. Health professions students’ use of social media. J Allied Health. 2011;40(2):78–81.

PubMed   Google Scholar  

Junco R, Elavsky C, Heiberger G. Putting twitter to the test: assessing outcomes for student collaboration, engagement and success. Br J Edu Technol. 2013;44(2):273–87.

Hay B, Carr P, Dawe L, Clark-Burg K. “iM ready to learn”: undergraduate nursing students knowledge, preferences, and practice of mobile technology and social media. Comput Inform Nurs. 2017;35(1):8–17.

Aaen J, Dalsgaard C. Student facebook groups as a third space: between social life and schoolwork. Learn Media Technol. 2016;41(1):160–86.

Flynn L, Jalali A, Moreau KA. Learning theory and its application to the use of social media in medical education. Postgrad Med J. 2015;91(1080):556–60.

Siemens G. Connectivism: learning theory or pastime for the self-amused? elearnspace: everything elearning. 2006.

Wenger E. Communities of practice: learning, meaning, and identity. New York, NY: Cambridge University Press; 1998.

Vygotsky L. Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press; 1978.

Lau K. Computer-based teaching module design: principles derived from learning theories. Med Educ. 2014;48(3):247–54.

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Giroux, C.M., Moreau, K.A. Nursing students’ use of social media in their learning: a case study of a Canadian School of Nursing. BMC Nurs 21 , 195 (2022). https://doi.org/10.1186/s12912-022-00977-0

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Social media post metrics:

• Engagement rate
• Impressions
• Video views
• Video reach

Profile metrics:

• Follower growth over time
• Negative feedback rate
• Profile visits
• Overall engagement rate

Best time to post recommendations

One of the most common reasons for the underperformance of social content is posting when your target audiences are not online or not interested in engaging with you.

This is why Hootsuite’s Best Time to Publish tool is one of the most popular features of Hootsuite Analytics. It looks at your unique historical social media data and recommends the optimal times to post based on three different goals:

• Link clicks

Most social media analytics tools only recommend posting times based on engagement. Or they’ll use data from universal benchmarks, instead of your unique performance history.

Other cool things you can do with Hootsuite Analytics:

• Customize report templates for only the metrics you care about
• Perform an easy competitive analysis and compare your performance to industry benchmarks
• Track the productivity of your social team (response times and resolution time for assigned posts, mentions, and comments)
• Monitor mentions, comments, and tags related to your business to avoid PR disasters before they happen

On top of all of that, Hootsuite won a 2024 TrustRadius Most Loved Award as well as 2023 Best Of Awards for Best Feature Set, Best Relationship, and Best Value for Price .

Competitive analysis

Hootsuite Analytics does Instagram, Facebook, and X (formerly Twitter) competitor analysis for you. You can track up to 20 competitors per network, and get a clear view of your strengths and weaknesses — plus actionable insights on the top posts, hashtags, and content formats in your niche.

Follow these 4 simple steps to track competitors with Hootsuite:

• Sign in to your Hootsuite account and pick Analytics from the main menu on the left side of the dashboard.
• Then, click on Competitive analysis in the Benchmarking section.
• At the top of the page, use the dropdown list of your social media profiles to select the one you want to compare to competitors.
• Then, pick the competitors you want to measure your performance against. To do that, go into the second dropdown list and check the boxes next to the competitors you want to view. To add competitors, click Manage competitors at the bottom of the dropdown box.

Then, type the name of a competitor into the search bar and select the correct profile from the dropdown list. Depending on your Hootsuite plan, you can add between 2 and 20 social accounts per network (Facebook, Instagram, and X) to your watchlist.

And that’s it! Now you can browse several competitive reports, including:

Overview , where you can see the number of posts you and your competitors posted in the selected timeframe (that can be adjusted in the top right corner of the dashboard) as well as every account’s posting frequency, average engagement, number of followers, and audience growth rate.

Post performance , where you can review your and your competitors’ top posts and sort results by reactions, comments, shares, and engagement — and quickly fetch inspiration for what to publish next.

Performance by post type , where you can find out what types of posts — photos, link posts, videos, text-only posts, and so on — are most popular with each brand’s audience. Results can be sorted to show which post types get the most reactions, shares, comments, or engagement.

Overall post performance , where you can see how you and your competitors did every day within the specified timeframe — all in one easy-to-read graph. You can drill down results by post type, or stick to the overall view.

Trending hashtags … which speaks for itself.

Source: Hootsuite Analytics

Post length , where you can find out how many characters and hashtags, on average, your competitors use in their posts.

Learn more about competitive analysis in Hootsuite Analytics .

Industry benchmarking

Need help setting realistic goals? Or maybe you’re not a fan of manually collecting data for audits and SWOT analyses ?

With Hootsuite’s social media benchmarking, you can find out how others in your industry are doing on social and compare your results with just a few clicks.

To get industry benchmarks, follow these steps:

• Sign in to your Hootsuite dashboard and head to Analytics .
• In the menu on the left side of the screen, scroll to Benchmarking and click Industry .
• Pick an industry that best describes your business.

Now you can see how your results compare to average performance stats within your industry. You can set up custom timeframes, switch between networks — Instagram, Facebook, X, LinkedIn, and TikTok — and look up benchmarks for the following metrics:

• Profile impressions
• Profile reach
• Audience growth rate
• Posting frequency

… and more.

You will also find tips and resources to improve your social media content performance right in the summary section:

And, if you need to present your results to your team, boss, or other stakeholders, you can easily download your comparison report as a PDF file.

Hootsuite Analytics is included in all Hootsuite plans . Try the best social media management tool for free for 30 days.

Learn more in this video or sign up for a Hootsuite free trial.

2. Sprout Social

Source: Sprout Social

Best for: Marketing teams at larger organizations

Coolest feature: Tag inbound and outbound social messages to track and analyze volume and performance patterns.

Price: Starting at $199/month

Sprout Social is another top contender in the battle of social media analytics tools, and it may be worth your consideration. Offering analytics for all the major social media platforms, Sprout can help you plan and execute your social media strategy.

Like Hootsuite, Sprout offers a full-featured analytics dashboard, which provides details on both your paid and organic posts and helps you decide when to publish content for the best results. You can also easily white-label and download reports from the Sprout dashboard.

Sprout is quite a bit more expensive than Hootsuite, but Hootsuite offers more features and integrations.

Learn more: Compare Hootsuite and Sprout to see which one works best for you.

Source: Buffer

Best for: Business owners who run their own social media, solo social media managers at small-to-medium-sized businesses, agencies

Coolest feature: Simple Instagram performance tracking, including Stories analytics

Price: Starting at $6/month for 1 social channel

Buffer is primarily a social media scheduler for Instagram, Facebook, X, TikTok, Pinterest, and LinkedIn.

When it comes to analytics, Buffer is relatively light on features. It doesn’t offer analytics for all platforms and doesn’t come with social listening features or competitive benchmarking. However, Buffer’s user-friendly dashboard is simple and straightforward, making it great for social media managers who just want to get in, schedule, and get out.

Learn more: Read our guide to Hootsuite vs. Buffer for more on how these platforms compare.

Source: HubSpot

Best for: Marketing teams at larger companies focused on understanding how social marketing efforts impact the customer journey

Coolest feature: Integration with your CRM to track data like new contacts driven by social media

Price: Starting at $800/month

Skill level: Advanced

Hubspot is a bit different from some of the other social media analytics tools on this list. With Hubspot, social media management is part of the Hubspot Marketing Hub software that also helps you manage email, SEO, and CRM records.

That means it’s best for brands that develop long-standing customer relationships, both before and after purchase, and that use multiple marketing approaches rather than sticking to social.

Hubspot integrates with Hootsuite to bring more social user context into your Hubspot CRM data and ticket system.

Learn more: You can add Hubspot to your Hootsuite dashboard

Source: Later

Best for: Business owners who run their own social media, solo social media managers at small-to-medium-sized businesses

Coolest feature: Link in Bio page data flow to track website clicks from Instagram and TikTok

Price: Starting at $25/month

Later really shines for smaller brands and creators who like to visualize and preview social media content before they post.

While Later can also help you measure the performance of your social media content and optimize posting times, the platform lacks some more advanced analytics features like competitive analysis and industry benchmarking.

Learn more: Compare Later and Hootsuite to see which solution is best for you.

6. Rival IQ

Source: Rival IQ

Best for: Social media managers who crave stats

Coolest feature: Free head-to-head reports against individual competitor accounts on Instagram, TikTok, Facebook, and X

Price: From $239 per month

Skill level: intermediate

Rival IQ was designed to let social media managers be data scientists, without the pesky certification. Rival IQ delivers on-demand analytical data, alerts, and custom reports from major social media platforms.

Easily conduct a competitive analysis or a complete social media audit with Rival IQ’s in-depth reporting. Then, present your findings to your stakeholders and marketing team with fully customizable charts, graphics, and dashboards.

Rival IQ isn’t just for the big picture. Comprehensive social post analytics lets you see exactly which posts work for each platform and identify why they work.

Pro tip: Getting owned by the competition? With Rival IQ you can also analyze your competitors’ social media accounts. See what works for them and look for ways to incorporate those techniques into your own social media presence.

Learn more: Try a demo or start your free trial with Rival IQ

7. Talkwalker

Source: Talkwalker

Best for: social media managers, PR and communications teams, brand monitors, product marketers, researchers

Coolest feature: Monitor conversations from more than 150 million sources to analyze engagement, potential reach, comments, sentiment, and emotions

Price: Pricing upon request –  request a demo for more details

Skill level: Intermediate to advanced

Talkwalker offers analytics related to social conversations beyond your owned social properties, including:

• Brand sentiment
• Important influencers
• Conversation clusters

You can filter by region, demographics, device, type of content, and more.

Talkwalker is especially useful to spot activity peaks in conversations about your brand. This can help you determine the best times for your brand to post on social media .

Psst: Hootsuite is set to acquire Talkwalker VERY SOON . This means that you will get access to Talkwalker social listening and analytics directly in your Hootsuite dashboard!

8. Brandwatch

Source: Brandwatch

Best for: PR and communications teams, social media marketers who focus on engagement and brand monitoring

Coolest feature: Track and analyze data from more than 100 million sources, including blogs, forums, and review sites, as well as social networks

Price: Pricing available on request – request a demo for more details

Brandwatch offers a powerful suite of tools that allow you to track and analyze your social media accounts while also monitoring brand reputation and social share of voice.

Brandwatch Consumer Research pulls from more than 1.4 trillion posts, with AI tools to help you filter out the trends and data that are most relevant to your business. You can set up email alerts to keep you informed when sentiment or conversion volume change.

Learn more: You can add Brandwatch to your Hootsuite dashboard

Source: Keyhole

Best for: Enterprise-level businesses and organizations

Coolest feature: Automated reports on influencer marketing campaigns with a breakdown of ROI

Price: Starting at $89/month

Keyhole lets you report on everything: social media campaigns, brand mentions and interactions, hashtag impact, and even influencer campaign results.

You can drill down into your impressions, reach, share of voice, and even analyze your competitors’ social media strategies.

If you’re using influencer marketing as part of your strategy, Keyhole has reporting capabilities that will let you identify the ideal influencers to work with and measure their performance over time.

Learn more: How to identify and work with the best influencers .

10. Channelview Insights

Source: Synaptive

Best for: YouTube marketers and creators, social media managers who run a YouTube channel alongside other social channels

Coolest feature: Analyze the performance of multiple YouTube channels and export PDF or CSV reports

Price: Starting at $8/month (free for Hootsuite Enterprise users)

Skill level: All skill levels

Channelview Insights allows you to analyze YouTube video and channel performance alongside all your other social media channels. You can also schedule automatic, regular reports.

Easily see the following metrics in one place:

• Views, engagement, subscription activity, and watch time
• Audience insights for demographics, geography, acquisition and more

Learn more: You can add Channelview Insights to your Hootsuite dashboard

11. Mentionlytics

Source: Mentionlytics

Best for: PR and communications teams, brand monitoring teams, product marketers, researchers at small to medium-sized businesses.

Coolest feature: Clear sentiment and share of voice analysis in multiple languages

Price : Starting at $69/month

Want to get the big picture view of what’s being said about your brand on the internet?

Mentionlytics is a great entry point to using social media analytics for brand monitoring — especially if you run a global business in more than one language.

It’s also an effective tool for identifying influencers and tracking relevant hashtags.

Learn more: You can add Mentionlytics to your Hootsuite dashboard

12. Panoramiq Insights

Best for: Instagram marketers and creators

Coolest feature: Detailed Instagram Story analytics for multiple accounts

Panoramiq Insights is perfect for Instagram marketers who want deeper insights on their Stories in particular.

Among other things, Panoramiq Insights lets you:

• Analyze follower demographics, including age, gender, country, city and language
• Monitor Instagram account activity (for multiple accounts), including views and new followers
• Find your best posts with view and engagement analytics
• Measure Story views and interactions

Learn more : You can add Panoramiq Insights to your Hootsuite dashboard

13. Quintly

Source: Quintly

Best for: Social media managers at small-to-medium-sized businesses, enterprise-level companies, agencies

Coolest feature: Customizable dashboards that draw from more than 500 social media metrics

Price: Starting at $315/month

Unlike many of the tools on this list, Quintly is exclusively a social media analytics tool. That means it’s built solely to provide top-quality analytics, rather than bundling analytics with other social media management capabilities.

Quintly provides detailed data and reports for Facebook, Instagram, Twitter, LinkedIn, YouTube and Snapchat, along with competitor benchmarking.

Learn more: The social media metrics you need to track in 2024

14. Iconosquare

Source: Iconosquare

Best for: Solo entrepreneurs who manage their own social media accounts, social media managers at small-to-medium-sized businesses

Coolest feature: Reports (in PDF or XLS) include social images for clearer reporting and analysis

Price: Starting at $79/month

Iconosquare allows you to report on brand metrics for multiple profiles across Instagram, Facebook, Twitter, LinkedIn, and TikTok. You can compare time periods and track more than 100 metrics as graphs or raw data.

While you’re at it, you can benchmark your performance against your competitors and set your reports to arrive in your inbox on a regular schedule.

Learn more: Social media benchmarks Q4 2023

7 free social media analytics tools

15. google analytics.

Source: Google

Best for: Social media professionals who work for a web-based business

Coolest feature: See how much traffic and leads flow to your website from your social media channels

Google Analytics is one of the best free tools to learn about your website visitors. If you’re a social marketer who wants to drive traffic to your website, it’s an invaluable resource.

While it’s not a standalone social media analytics tool, you can use it to set up reports that will help you:

• See which social media platforms send you the most traffic
• See what content drives the most leads and traffic on which social networks
• Get to know your audience with demographic data
• Calculate the ROI of your social media campaigns

With these data points, you’ll be able to get the most out of your social media campaigns and effectively strategize for the future. No social media strategy is complete without Google Analytics.

Learn more: How to use Google Analytics to track social media success

16. Meta Business Suite Insights

Source: Meta Business Suite

Available to: Facebook Pages and Instagram professional accounts

The Insights tab within Meta Business Suite is the place to find account-, platform-, and post-level metrics for Facebook and Instagram side-by-side. You can also research the demographics of your audience and track your ad account spend.

Learn more: 3 Top Facebook analytics tools

17. Instagram Insights

Source: Instagram

Available to: Business and creator accounts

Instagram’s in-app analytics tool offers account- and post-level data for metrics like reach and engagement. You can track trends in follower growth and identify all the different ways followers interact with your content.

You can also learn about the demographics of your Instagram audience and track the performance of your Instagram Reels and Stories.

Learn more: Guide to Smarter Results Tracking on Instagram

18. TikTok Analytics

Source: TikTok

Available to: TikTok business accounts

TikTok’s native analytics tool breaks your metrics down into overview data, content performance analytics, and follower demographics and growth.

Learn more: 4 TikTok analytics tools

19. X Analytics

Available to: All users of X (formerly Twitter)

While X analytics are currently being modified, for the moment they allow you to understand the performance of your paid and organic X posts and learn which other X users have the most potential to amplify your content.

You can access monthly highlights like top posts and top followers. It’s a good place to get a snapshot of your best performing content and identify potential influencers or brand ambassadors .

You can also dig deeper to track the engagements and impressions on your content over a selected period.

Learn more: How to use X analytics

20. Pinterest Analytics

Source: Pinterest

Available to: Pinterest business accounts

Pinterest’s built-in free social media analytics tools help you understand your Pinterest audience’s interests. You can track key metrics for paid and organic Pins, including impressions, engagements, video views, and profile visits. You’ll also find Pinterest-specific stats like saves and closeups.

If you add the Pinterest tag to your website, you can use Pinterest Analytics to track conversions.

Learn more: A Simple Guide to Using Pinterest Analytics

21. LinkedIn Page Analytics

Source: LinkedIn

Available to: LinkedIn Page admins

LinkedIn Page Analytics provides data on your Linkedin content, followers, visitors, leads, and competitors. You can also track your employee advocacy efforts, engagement with your career pages, and newsletter performance.

Learn more: LinkedIn Analytics: The Complete Guide for Marketers

Track your social media performance and maximize your budget with Hootsuite. Publish your posts and analyze the results in the same, easy-to-use dashboard. Try it free today.

All your social media analytics in one place . Use Hootsuite to see what’s working and where to improve performance.

Become a better social marketer.

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Christina Newberry is an award-winning writer and editor whose greatest passions include food, travel, urban gardening, and the Oxford comma—not necessarily in that order.

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The state of AI in 2023: Generative AI’s breakout year

You have reached a page with older survey data. please see our 2024 survey results here ..

The latest annual McKinsey Global Survey  on the current state of AI confirms the explosive growth of generative AI (gen AI) tools . Less than a year after many of these tools debuted, one-third of our survey respondents say their organizations are using gen AI regularly in at least one business function. Amid recent advances, AI has risen from a topic relegated to tech employees to a focus of company leaders: nearly one-quarter of surveyed C-suite executives say they are personally using gen AI tools for work, and more than one-quarter of respondents from companies using AI say gen AI is already on their boards’ agendas. What’s more, 40 percent of respondents say their organizations will increase their investment in AI overall because of advances in gen AI. The findings show that these are still early days for managing gen AI–related risks, with less than half of respondents saying their organizations are mitigating even the risk they consider most relevant: inaccuracy.

The organizations that have already embedded AI capabilities have been the first to explore gen AI’s potential, and those seeing the most value from more traditional AI capabilities—a group we call AI high performers—are already outpacing others in their adoption of gen AI tools. 1 We define AI high performers as organizations that, according to respondents, attribute at least 20 percent of their EBIT to AI adoption.

The expected business disruption from gen AI is significant, and respondents predict meaningful changes to their workforces. They anticipate workforce cuts in certain areas and large reskilling efforts to address shifting talent needs. Yet while the use of gen AI might spur the adoption of other AI tools, we see few meaningful increases in organizations’ adoption of these technologies. The percent of organizations adopting any AI tools has held steady since 2022, and adoption remains concentrated within a small number of business functions.

Table of Contents

• It’s early days still, but use of gen AI is already widespread
• Leading companies are already ahead with gen AI
• AI-related talent needs shift, and AI’s workforce effects are expected to be substantial
• With all eyes on gen AI, AI adoption and impact remain steady

About the research

1. it’s early days still, but use of gen ai is already widespread.

The findings from the survey—which was in the field in mid-April 2023—show that, despite gen AI’s nascent public availability, experimentation with the tools  is already relatively common, and respondents expect the new capabilities to transform their industries. Gen AI has captured interest across the business population: individuals across regions, industries, and seniority levels are using gen AI for work and outside of work. Seventy-nine percent of all respondents say they’ve had at least some exposure to gen AI, either for work or outside of work, and 22 percent say they are regularly using it in their own work. While reported use is quite similar across seniority levels, it is highest among respondents working in the technology sector and those in North America.

Organizations, too, are now commonly using gen AI. One-third of all respondents say their organizations are already regularly using generative AI in at least one function—meaning that 60 percent of organizations with reported AI adoption are using gen AI. What’s more, 40 percent of those reporting AI adoption at their organizations say their companies expect to invest more in AI overall thanks to generative AI, and 28 percent say generative AI use is already on their board’s agenda. The most commonly reported business functions using these newer tools are the same as those in which AI use is most common overall: marketing and sales, product and service development, and service operations, such as customer care and back-office support. This suggests that organizations are pursuing these new tools where the most value is. In our previous research , these three areas, along with software engineering, showed the potential to deliver about 75 percent of the total annual value from generative AI use cases.

In these early days, expectations for gen AI’s impact are high : three-quarters of all respondents expect gen AI to cause significant or disruptive change in the nature of their industry’s competition in the next three years. Survey respondents working in the technology and financial-services industries are the most likely to expect disruptive change from gen AI. Our previous research shows  that, while all industries are indeed likely to see some degree of disruption, the level of impact is likely to vary. 2 “ The economic potential of generative AI: The next productivity frontier ,” McKinsey, June 14, 2023. Industries relying most heavily on knowledge work are likely to see more disruption—and potentially reap more value. While our estimates suggest that tech companies, unsurprisingly, are poised to see the highest impact from gen AI—adding value equivalent to as much as 9 percent of global industry revenue—knowledge-based industries such as banking (up to 5 percent), pharmaceuticals and medical products (also up to 5 percent), and education (up to 4 percent) could experience significant effects as well. By contrast, manufacturing-based industries, such as aerospace, automotives, and advanced electronics, could experience less disruptive effects. This stands in contrast to the impact of previous technology waves that affected manufacturing the most and is due to gen AI’s strengths in language-based activities, as opposed to those requiring physical labor.

Responses show many organizations not yet addressing potential risks from gen AI

According to the survey, few companies seem fully prepared for the widespread use of gen AI—or the business risks these tools may bring. Just 21 percent of respondents reporting AI adoption say their organizations have established policies governing employees’ use of gen AI technologies in their work. And when we asked specifically about the risks of adopting gen AI, few respondents say their companies are mitigating the most commonly cited risk with gen AI: inaccuracy. Respondents cite inaccuracy more frequently than both cybersecurity and regulatory compliance, which were the most common risks from AI overall in previous surveys. Just 32 percent say they’re mitigating inaccuracy, a smaller percentage than the 38 percent who say they mitigate cybersecurity risks. Interestingly, this figure is significantly lower than the percentage of respondents who reported mitigating AI-related cybersecurity last year (51 percent). Overall, much as we’ve seen in previous years, most respondents say their organizations are not addressing AI-related risks.

2. Leading companies are already ahead with gen AI

The survey results show that AI high performers—that is, organizations where respondents say at least 20 percent of EBIT in 2022 was attributable to AI use—are going all in on artificial intelligence, both with gen AI and more traditional AI capabilities. These organizations that achieve significant value from AI are already using gen AI in more business functions than other organizations do, especially in product and service development and risk and supply chain management. When looking at all AI capabilities—including more traditional machine learning capabilities, robotic process automation, and chatbots—AI high performers also are much more likely than others to use AI in product and service development, for uses such as product-development-cycle optimization, adding new features to existing products, and creating new AI-based products. These organizations also are using AI more often than other organizations in risk modeling and for uses within HR such as performance management and organization design and workforce deployment optimization.

AI high performers are much more likely than others to use AI in product and service development.

Another difference from their peers: high performers’ gen AI efforts are less oriented toward cost reduction, which is a top priority at other organizations. Respondents from AI high performers are twice as likely as others to say their organizations’ top objective for gen AI is to create entirely new businesses or sources of revenue—and they’re most likely to cite the increase in the value of existing offerings through new AI-based features.

As we’ve seen in previous years , these high-performing organizations invest much more than others in AI: respondents from AI high performers are more than five times more likely than others to say they spend more than 20 percent of their digital budgets on AI. They also use AI capabilities more broadly throughout the organization. Respondents from high performers are much more likely than others to say that their organizations have adopted AI in four or more business functions and that they have embedded a higher number of AI capabilities. For example, respondents from high performers more often report embedding knowledge graphs in at least one product or business function process, in addition to gen AI and related natural-language capabilities.

While AI high performers are not immune to the challenges of capturing value from AI, the results suggest that the difficulties they face reflect their relative AI maturity, while others struggle with the more foundational, strategic elements of AI adoption. Respondents at AI high performers most often point to models and tools, such as monitoring model performance in production and retraining models as needed over time, as their top challenge. By comparison, other respondents cite strategy issues, such as setting a clearly defined AI vision that is linked with business value or finding sufficient resources.

The findings offer further evidence that even high performers haven’t mastered best practices regarding AI adoption, such as machine-learning-operations (MLOps) approaches, though they are much more likely than others to do so. For example, just 35 percent of respondents at AI high performers report that where possible, their organizations assemble existing components, rather than reinvent them, but that’s a much larger share than the 19 percent of respondents from other organizations who report that practice.

Many specialized MLOps technologies and practices  may be needed to adopt some of the more transformative uses cases that gen AI applications can deliver—and do so as safely as possible. Live-model operations is one such area, where monitoring systems and setting up instant alerts to enable rapid issue resolution can keep gen AI systems in check. High performers stand out in this respect but have room to grow: one-quarter of respondents from these organizations say their entire system is monitored and equipped with instant alerts, compared with just 12 percent of other respondents.

3. AI-related talent needs shift, and AI’s workforce effects are expected to be substantial

Our latest survey results show changes in the roles that organizations are filling to support their AI ambitions. In the past year, organizations using AI most often hired data engineers, machine learning engineers, and Al data scientists—all roles that respondents commonly reported hiring in the previous survey. But a much smaller share of respondents report hiring AI-related-software engineers—the most-hired role last year—than in the previous survey (28 percent in the latest survey, down from 39 percent). Roles in prompt engineering have recently emerged, as the need for that skill set rises alongside gen AI adoption, with 7 percent of respondents whose organizations have adopted AI reporting those hires in the past year.

The findings suggest that hiring for AI-related roles remains a challenge but has become somewhat easier over the past year, which could reflect the spate of layoffs at technology companies from late 2022 through the first half of 2023. Smaller shares of respondents than in the previous survey report difficulty hiring for roles such as AI data scientists, data engineers, and data-visualization specialists, though responses suggest that hiring machine learning engineers and AI product owners remains as much of a challenge as in the previous year.

Looking ahead to the next three years, respondents predict that the adoption of AI will reshape many roles in the workforce. Generally, they expect more employees to be reskilled than to be separated. Nearly four in ten respondents reporting AI adoption expect more than 20 percent of their companies’ workforces will be reskilled, whereas 8 percent of respondents say the size of their workforces will decrease by more than 20 percent.

Looking specifically at gen AI’s predicted impact, service operations is the only function in which most respondents expect to see a decrease in workforce size at their organizations. This finding generally aligns with what our recent research  suggests: while the emergence of gen AI increased our estimate of the percentage of worker activities that could be automated (60 to 70 percent, up from 50 percent), this doesn’t necessarily translate into the automation of an entire role.

AI high performers are expected to conduct much higher levels of reskilling than other companies are. Respondents at these organizations are over three times more likely than others to say their organizations will reskill more than 30 percent of their workforces over the next three years as a result of AI adoption.

4. With all eyes on gen AI, AI adoption and impact remain steady

While the use of gen AI tools is spreading rapidly, the survey data doesn’t show that these newer tools are propelling organizations’ overall AI adoption. The share of organizations that have adopted AI overall remains steady, at least for the moment, with 55 percent of respondents reporting that their organizations have adopted AI. Less than a third of respondents continue to say that their organizations have adopted AI in more than one business function, suggesting that AI use remains limited in scope. Product and service development and service operations continue to be the two business functions in which respondents most often report AI adoption, as was true in the previous four surveys. And overall, just 23 percent of respondents say at least 5 percent of their organizations’ EBIT last year was attributable to their use of AI—essentially flat with the previous survey—suggesting there is much more room to capture value.

Organizations continue to see returns in the business areas in which they are using AI, and they plan to increase investment in the years ahead. We see a majority of respondents reporting AI-related revenue increases within each business function using AI. And looking ahead, more than two-thirds expect their organizations to increase their AI investment over the next three years.

The online survey was in the field April 11 to 21, 2023, and garnered responses from 1,684 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. Of those respondents, 913 said their organizations had adopted AI in at least one function and were asked questions about their organizations’ AI use. To adjust for differences in response rates, the data are weighted by the contribution of each respondent’s nation to global GDP.

The survey content and analysis were developed by Michael Chui , a partner at the McKinsey Global Institute and a partner in McKinsey’s Bay Area office, where Lareina Yee is a senior partner; Bryce Hall , an associate partner in the Washington, DC, office; and senior partners Alex Singla and Alexander Sukharevsky , global leaders of QuantumBlack, AI by McKinsey, based in the Chicago and London offices, respectively.

They wish to thank Shivani Gupta, Abhisek Jena, Begum Ortaoglu, Barr Seitz, and Li Zhang for their contributions to this work.

This article was edited by Heather Hanselman, an editor in the Atlanta office.

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