Literature DB >> 35834505

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

Beidi Dong1, Xiaoyun Wu2.   

Abstract

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 25th, 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.

Entities:  

Mesh：

Year:  2022        PMID： 35834505      PMCID： PMC9282545          DOI： 10.1371/journal.pone.0269288

Source DB:  PubMed          Journal:  PLoS One        ISSN： 1932-6203            Impact factor:   3.752


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.

Results

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.
Fig 1

The number of tweets posted by the 115 major police departments in the U.S. before and after the killing of George Floyd on May 25th, 2020 (above: Daily information; bottom: Weekly information).

Fig 2

Public reactions (i.e., average number of favorites per tweet) to tweets posted by the 115 major police departments in the U.S. before and after the killing of George Floyd on May 25th, 2020 (above: Daily information; bottom: Weekly information).

Fig 3

Public reactions (i.e., average number of retweets per tweet) to tweets posted by the 115 major police departments in the U.S. before and after the killing of George Floyd on May 25th, 2020 (above: Daily information; bottom: Weekly information).

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.
Fig 4

The negative-to-positive words ratio in the tweets of the 115 major police departments in the U.S. before and after the killing of George Floyd on May 25th, 2020 (above: Daily information; bottom: Weekly information).

Fig 5

Emotional valence in the tweets of the 115 major police departments in the U.S. before and after the killing of George Floyd on May 25th, 2020 (above: Daily information; bottom: Weekly information).

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.
Table 1

Accuracy and kappa of the random forest classifier.

KappaAccuracy (overall)Accuracy (c1)Accuracy (c2)Accuracy (c3)Accuracy (c4)Accuracy (c5)Accuracy (c6)Accuracy (c7)
Cross validation0.7670.8140.7820.7390.8190.6460.7940.8110.907
Split test set0.7580.8080.7660.7390.8660.5800.7590.8190.901

Note: The 7 categories (or focal issues) 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.

Table 2

Number of tweets classified into each category.

Frequency (overall)Percentage (overall)Frequency (pre-kill)Percentage (pre-kill)Frequency (post-kill)Percentage (post-kill)
Class 122075.82%450.26%216210.58%
Class 224666.51%199311.42%4732.31%
Class 3455112.01%180010.31%275113.46%
Class 4445911.77%208211.93%237711.63%
Class 530548.06%12637.23%17918.76%
Class 6760220.06%304617.45%455622.29%
Class 71356035.78%722841.40%633230.98%
37899100%17457100%20442100%

Note: The 7 categories (or focal issues) 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.

Note: The 7 categories (or focal issues) 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. Note: The 7 categories (or focal issues) 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. 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.
Fig 6

Proportions of focal issues mentioned in the tweets of the 115 major police departments in the U.S. before and after the killing of George Floyd on May 25th, 2020.

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.

Fig 7

Distribution of police departments in relation to the changes in the focal issues of tweets posted by the 115 major police departments in the U.S. after the killing of George Floyd on May 25th, 2020.

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.

Fig 8

Public reactions by focal issues of the tweets posted by the 115 major police departments in the U.S. before and after the killing of George Floyd on May 25th, 2020.

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.

Proportions of focal issues mentioned in the tweets of the 115 major police departments in the U.S. before and after the killing of George Floyd on May 25th, 2020.

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.

Distribution of police departments in relation to the changes in the focal issues of tweets posted by the 115 major police departments in the U.S. after the killing of George Floyd on May 25th, 2020.

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.

Public reactions by focal issues of the tweets posted by the 115 major police departments in the U.S. before and after the killing of George Floyd on May 25th, 2020.

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.

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.
Table 3

Agencies (in the higher-use group) ranked by the increase in the number of tweets posted before and after the killing.

#Agency nameTotal number of tweets pre-killingTotal number of tweets post-killingNumber of tweets per day pre-killingNumber of tweets per day post-killingFrequency changePercentage change
1Aurora Police Dept.1524772.767.124.36158
2Portland Police Dept.3059155.5513.78.11146
3Milwaukee Police Dept.4288127.7812.14.3455.7
4Seattle Police Dept.1212272.23.391.1954
5Charlotte-Mecklenburg Police Dept.1963253.564.851.2936.1
6Memphis Police Dept.1181912.152.850.70532.9
7Jefferson County(CO) Sheriff’s Office1312082.383.10.72330.3
8Omaha Police Dept.2163413.935.091.1629.6
9Kansas City Police Dept.27542656.361.3627.2
10Montgomery County(MD) Police Dept.1812723.294.060.76923.4
11Denver Police Dept.847125915.418.83.3922
12Austin Police Dept.1682433.053.630.57218.7
13Baltimore Police Dept.1632322.963.460.49916.8
14D.C. Metropolitan Police Dept.778108914.116.32.1114.9
15Raleigh Police Dept.1722273.133.390.2618.34
16Prince William County Police Dept.2573384.675.040.3727.96
17Gwinnett County Police Dept.1201572.182.340.1617.4
18Oklahoma City Police Dept.1822243.313.340.03421.03
19Washington County Sheriff’s Office1291542.352.3-0.0469-2
20Bakersfield Police Dept.1351612.452.4-0.0516-2.1
21Palm Beach County Sheriff’s Office1802123.273.16-0.109-3.32
22Dallas Police Dept.4254937.737.36-0.369-4.78
23Jacksonville Sheriff’s Office1431642.62.45-0.152-5.86
24Jefferson County(AL) Sheriff’s Dept.1261442.292.15-0.142-6.18
25Chicago Police Dept.1681913.052.85-0.204-6.67
26Hillsborough County Sheriff’s Office2332644.243.94-0.296-6.99
27Orange County(FL) Sheriff’s Office57663810.59.52-0.95-9.07
28Manatee County(FL) Sheriff’s Office1161282.111.91-0.199-9.42
29Honolulu Police Dept.1962153.563.21-0.355-9.95
30Houston Police Dept.4534858.247.24-0.998-12.1
31Loudoun County Sheriff’s Office1141212.071.81-0.267-12.9
32Bernalillo County Sheriff’s Dept.2102213.823.3-0.52-13.6
33Columbus Police Dept.2963115.384.64-0.74-13.8
34Boston Police Dept.2142243.893.34-0.548-14.1
35Prince George’s County Police Dept.22022843.4-0.597-14.9
36Douglas County(CO) Sheriff’s Office1181152.151.72-0.429-20
37Broward County Sheriff’s Office1731683.152.51-0.638-20.3
38San Diego County Sheriff’s Dept.1391332.531.99-0.542-21.5
39Phoenix Police Dept.1841733.352.58-0.763-22.8
40Alameda County Sheriff’s Office1811683.292.51-0.783-23.8
41El Paso County Sheriff’s Office1331212.421.81-0.612-25.3
42Fairfax County Police Dept.3673186.674.75-1.93-28.9
43San Diego Police Dept.2261954.112.91-1.2-29.2
44Harris county Sheriff’s Office2241924.072.87-1.21-29.6
45Tampa Police Dept.1109421.4-0.597-29.9
46Montgomery County (TX) Sheriff’s Office1251042.271.55-0.72-31.7
47Fort Worth Police Dept.1971603.582.39-1.19-33.3
48Las Vegas Police Dept.112902.041.34-0.693-34
49Los Angeles County Sheriff’s Dept.2662124.843.16-1.67-34.6
50Henrico County Police Dept.1451142.641.7-0.935-35.5
51Sacramento Police Dept.1531142.781.7-1.08-38.8
52Anne Arundel Police Dept.1981443.62.15-1.45-40.3
53Baltimore County Police Dept.22016042.39-1.61-40.3
54New York Police Dept.66343212.16.45-5.61-46.5
55Richland County Sheriff’s Dept.68744312.56.61-5.88-47.1
56Chesterfield County Police Dept.119672.161-1.16-53.8
57Miami Police Dept.49527094.03-4.97-55.2
58Pierce County Sheriff’s Dept.153782.781.16-1.62-58.2
59Wichita Police Dept.166813.021.21-1.81-59.9
60Pinellas County Police Dept.228414.150.612-3.53-85.2
Table 12

Agencies (in the lower-use group) ranked by the increase in posting category 7 (community engagement and outreach) tweets before and after the killing.

#Agency nameTotal number of tweets pre-killingTotal number of tweets post-killingNumber of C7 tweets pre-killingNumber of C7 tweets post-killingPercentage of C7 tweets pre-killingPercentage of C7 tweets post-killingPercentage change
1San Jose Police Dept.192713220.6840.8150.131
2Santa Clara County Sheriff’s Office311918130.5810.6840.104
3Hennepin County Sheriff’s Office614043320.7050.80.0951
4Osceola County Sheriff’s Office706730320.4290.4780.049
5Suffolk County Police Dept.704351330.7290.7670.0389
6Arapahoe County Sheriff’s Office667247540.7120.750.0379
7Ventura County Sheriff’s Office7811519320.2440.2780.0347
8Unified (Salt Lake, Utah) Police Dept.33171580.4550.4710.016
9Collier County Sheriff’s Office497817280.3470.3590.012
10Kern County Sheriff’s Dept.917539330.4290.440.0114
11Lee County(FL) Sheriff’s Office816664520.790.788-0.00224
12Orange County(CA) Sheriff’s Dept.568733510.5890.586-0.00308
13Dekalb County Police Dept.697124230.3480.324-0.0239
14Saint Paul Police Dept.3610511290.3060.276-0.0294
15Pima County Sheriff’s Dept.6517022510.3380.3-0.0385
16Philadelphia Police Dept.62130790.1130.0692-0.0437
17Arlington Police Dept.8815557930.6480.6-0.0477
18New Castle County Police Dept.574517110.2980.244-0.0538
19Adams County Sheriff’s Office9412766820.7020.646-0.0565
20Riverside(CA) Police Dept.315512180.3870.327-0.0598
21East Baton Rouge Sheriff’s Office622433110.5320.458-0.0739
22Atlanta Police Dept.336921380.6360.551-0.0856
23Franklin County Sheriff’s Office757043330.5730.471-0.102
24Minneapolis Police Dept.194810200.5260.417-0.11
25San Francisco Police Dept.9210154480.5870.475-0.112
26Howard County Police Dept.50302190.420.3-0.12
27Sacramento County Sheriff’s Office37201240.3240.2-0.124
28Los Angeles Police Dept.8917540560.4490.32-0.129
29Santa Ana Police Dept.9912053480.5350.4-0.135
30Volusia County Sheriff’s Office947137180.3940.254-0.14
31San Antonio Police Dept.213610120.4760.333-0.143
32El Paso Police Dept.617334290.5570.397-0.16
33Washoe County Sheriff’s Office8113162790.7650.603-0.162
34Oakland(CA) Police Dept.659538400.5850.421-0.164
35Shelby County(TN) Sheriff’s Office437615140.3490.184-0.165
36Virginia Beach Police Dept.419514160.3410.168-0.173
37St. Louis County Police Dept.939767530.720.546-0.174
38Detroit Police Dept.427127330.6430.465-0.178
39Metropolitan Nashville Police Dept.10511856400.5330.339-0.194
40Pittsburgh Bureau of Police7912833280.4180.219-0.199
41Tulsa Police Dept.4610122270.4780.267-0.211
42Tucson Police Dept.43372090.4650.243-0.222
43Albuquerque Police Dept.794942150.5320.306-0.226
44Seminole County Sheriff’s Office332322100.6670.435-0.232
45Louisville Metropolitan Police Dept.204110100.50.244-0.256
46Corpus Christi Police Dept.454027130.60.325-0.275
47Lexington Police Dept.387222180.5790.25-0.329
48St. Louis Police Dept.819040140.4940.156-0.338
49Mesa Police Dept.1014172150.7130.366-0.347
50Stockton(CA) Police Dept.35531540.4290.0755-0.353
51Travis County Sheriff’s Office203215120.750.375-0.375
52Colorado Springs Police Dept.8511854300.6350.254-0.381
53Anaheim Police Dept.57473580.6140.17-0.444
54Cleveland Police Dept.187512100.6670.133-0.533
55Long Beach Police Dept.4123228210.6830.0905-0.592
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.
Table 4

Agencies (in the lower-use group) ranked by the increase in the number of tweets posted before and after the killing.

#Agency nameTotal number of tweets pre-killingTotal number of tweets post-killingNumber of tweets per day pre-killingNumber of tweets per day post-killingFrequency changePercentage change
1Long Beach Police Dept.412330.7453.482.73367
2Cleveland Police Dept.18790.3271.180.852260
3Saint Paul Police Dept.361090.6551.630.972149
4Pima County Sheriff’s Dept.661731.22.581.38115
5Minneapolis Police Dept.19480.3450.7160.371107
6Virginia Beach Police Dept.431060.7821.580.8102
7Atlanta Police Dept.33710.61.060.4676.6
8Louisville Metropolitan Police Dept.21450.3820.6720.2975.9
9Philadelphia Police Dept.621301.131.940.81372.1
10Tulsa Police Dept.501040.9091.550.64370.7
11Los Angeles Police Dept.911811.652.71.0563.3
12Lexington Police Dept.38730.6911.090.39957.7
13San Antonio Police Dept.21380.3820.5670.18548.5
14Riverside(CA) Police Dept.31560.5640.8360.27248.3
15Arlington Police Dept.881551.62.310.71344.6
16Washoe County Sheriff’s Office811401.472.090.61741.9
17Detroit Police Dept.43740.7821.10.32341.3
18Shelby County(TN) Sheriff’s Office45760.8181.130.31638.6
19San Jose Police Dept.21350.3820.5220.14136.8
20Pittsburgh Bureau of Police801281.451.910.45631.3
21Travis County Sheriff’s Office20320.3640.4780.11431.3
22Collier County Sheriff’s Office50780.9091.160.25528.1
23Orange County(CA) Sheriff’s Dept.58881.051.310.25924.5
24Ventura County Sheriff’s Office781171.421.750.32823.1
25Stockton(CA) Police Dept.36530.6550.7910.13620.9
26Oakland(CA) Police Dept.67951.221.420.216.4
27Colorado Springs Police Dept.851181.551.760.21614
28Adams County Sheriff’s Office971341.7620.23613.4
29El Paso Police Dept.65811.181.210.02712.3
30Santa Ana Police Dept.991221.81.820.02091.16
31Metropolitan Nashville Police Dept.1051181.911.76-0.148-7.75
32San Francisco Police Dept.921011.671.51-0.165-9.88
33Arapahoe County Sheriff’s Office68731.241.09-0.147-11.9
34St. Louis Police Dept.84901.531.34-0.184-12
35St. Louis County Police Dept.93991.691.48-0.213-12.6
36Dekalb County Police Dept.76741.381.1-0.277-20.1
37Osceola County Sheriff’s Office70671.271-0.273-21.4
38Franklin County Sheriff’s Office75711.361.06-0.304-22.3
39Corpus Christi Police Dept.45420.8180.627-0.191-23.4
40Tucson Police Dept.43370.7820.552-0.23-29.4
41Kern County Sheriff’s Dept.91751.651.12-0.535-32.3
42Lee County(FL) Sheriff’s Office81661.470.985-0.488-33.1
43Anaheim Police Dept.62501.130.746-0.381-33.8
44New Castle County Police Dept.58461.050.687-0.368-34.9
45Volusia County Sheriff’s Office95711.731.06-0.668-38.6
46Seminole County Sheriff’s Office33230.60.343-0.257-42.8
47Hennepin County Sheriff’s Office61401.110.597-0.512-46.2
48Suffolk County Police Dept.80511.450.761-0.693-47.7
49Albuquerque Police Dept.79491.440.731-0.705-49.1
50Howard County Police Dept.50300.9090.448-0.461-50.7
51Santa Clara County Sheriff’s Office32190.5820.284-0.298-51.3
52Sacramento County Sheriff’s Office37210.6730.313-0.359-53.4
53Unified (Salt Lake, Utah) Police Dept.35180.6360.269-0.368-57.8
54Mesa Police Dept.107471.950.701-1.24-63.9
55East Baton Rouge Sheriff’s Office62241.130.358-0.769-68.2
Table 5

Agencies (in the higher-use group) ranked by the increase in the received favorites per tweet before and after the killing.

#Agency nameAverage number of favorites received per tweet pre-killingAverage number of favorites received per tweet post-killingRaw changePercentage change
1Portland Police Dept.35.8236200559
2Seattle Police Dept.65.3380314482
3Charlotte-Mecklenburg Police Dept.9.7747.137.4383
4Tampa Police Dept.22.992.469.5304
5San Diego Police Dept.55.2197142257
6Austin Police Dept.21.275.254.1255
7Pinellas County Police Dept.6.772114.2209
8Milwaukee Police Dept.5.6417.411.8209
9Columbus Police Dept.22.661.438.8172
10Wichita Police Dept.16.544.728.3172
11Dallas Police Dept.28.673.544.9157
12Oklahoma City Police Dept.2665.739.7153
13Alameda County Sheriff’s Office26.359.633.3127
14New York Police Dept.103231128124
15Omaha Police Dept.33.170.637.4113
16D.C. Metropolitan Police Dept.14.931.216.3109
17Miami Police Dept.14.430.115.6108
18Denver Police Dept.7.8816.48.47108
19Hillsborough County Sheriff’s Office21.942.720.894.7
20Baltimore Police Dept.2140.519.593.2
21Gwinnett County Police Dept.1832.514.479.9
22Boston Police Dept.7813759.476.1
23Sacramento Police Dept.29.852.422.675.9
24Phoenix Police Dept.84.514863.975.6
25Memphis Police Dept.3.536.112.5873.3
26Houston Police Dept.48.682.834.270.5
27Fort Worth Police Dept.54.390.736.467
28Jefferson County(AL) Sheriff’s Dept.3863.425.366.7
29Chicago Police Dept.11217663.556.6
30Chesterfield County Police Dept.10.816.55.7553.4
31Aurora Police Dept.19.228.18.9346.5
32San Diego County Sheriff’s Dept.36.351.615.342.2
33Douglas County(CO) Sheriff’s Office33.246.513.340.1
34Kansas City Police Dept.96.313437.939.3
35Las Vegas Police Dept.10714538.435.9
36Prince George’s County Police Dept.13.618.24.6534.2
37Fairfax County Police Dept.27.334.87.4227.2
38Pierce County Sheriff’s Dept.82.410320.925.3
39Richland County Sheriff’s Dept.15418632.521.2
40Los Angeles County Sheriff’s Dept.57.168.11119.2
41Prince William County Police Dept.12.814.92.0716.2
42Harris county Sheriff’s Office33.238.24.9815
43Honolulu Police Dept.1112.61.6114.6
44Palm Beach County Sheriff’s Office64.773.78.9713.9
45Orange County(FL) Sheriff’s Office22.324.62.3410.5
46Baltimore County Police Dept.12.8141.169.01
47Bakersfield Police Dept.7.658.170.5226.82
48Montgomery County (TX) Sheriff’s Office5.105.430.3376.61
49Jefferson County(CO) Sheriff’s Office42.344.82.495.87
50Jacksonville Sheriff’s Office43.245.42.225.14
51Manatee County(FL) Sheriff’s Office15.215.40.2271.5
52Loudoun County Sheriff’s Office12.612.2-0.354-2.82
53Raleigh Police Dept.31.229.2-2.02-6.46
54Montgomery County(MD) Police Dept.22.420.9-1.49-6.63
55Bernalillo County Sheriff’s Dept.9.028.39-0.635-7.03
56El Paso County Sheriff’s Office29.623.7-5.84-19.7
57Broward County Sheriff’s Office78.360.8-17.5-22.4
58Washington County Sheriff’s Office5340.6-12.5-23.5
59Anne Arundel Police Dept.22.115.7-6.39-28.9
60Henrico County Police Dept.8.125.51-2.61-32.1
Table 6

Agencies (in the lower-use group) ranked by the increase in the received favorites per tweet before and after the killing.

#Agency nameAverage number of favorites received per tweet pre-killingAverage number of favorites received per tweet post-killingRaw changePercentage change
1Ventura County Sheriff’s Office11.51391281117
2Saint Paul Police Dept.19137118619
3Atlanta Police Dept.40222182455
4Minneapolis Police Dept.68.5347279407
5Louisville Metropolitan Police Dept.31.5147116368
6Unified (Salt Lake, Utah) Police Dept.7.2332.825.6354
7Philadelphia Police Dept.23.710278.6331
8Anaheim Police Dept.40.4164124306
9Stockton(CA) Police Dept.13.849.335.5257
10Lexington Police Dept.15.655.640256
11St. Louis Police Dept.34.611176.3221
12Cleveland Police Dept.56.6172116204
13Tulsa Police Dept.82.6237155187
14Metropolitan Nashville Police Dept.109306197181
15San Jose Police Dept.5713881.3143
16Pima County Sheriff’s Dept.10.324.714.4139
17Howard County Police Dept.2454.830.9129
18Albuquerque Police Dept.59.913676.4127
19Osceola County Sheriff’s Office5.8312.26.41110
20San Antonio Police Dept.57.612062.4108
21St. Louis County Police Dept.5812061.8107
22Seminole County Sheriff’s Office18.43314.679.7
23Oakland(CA) Police Dept.42.172.630.572.4
24Colorado Springs Police Dept.32.650.918.356.1
25Riverside(CA) Police Dept.22.533.911.450.5
26Los Angeles Police Dept.30844713945.1
27Detroit Police Dept.36.351.815.442.5
28Santa Clara County Sheriff’s Office37.353.115.842.4
29Hennepin County Sheriff’s Office18.926.57.5740.1
30Franklin County Sheriff’s Office83.211532.138.6
31Long Beach Police Dept.13.618.64.9936.8
32Santa Ana Police Dept.27.93810.136.1
33San Francisco Police Dept.5368.515.629.4
34Dekalb County Police Dept.14.818.43.5223.8
35Mesa Police Dept.48.759.811.122.9
36Corpus Christi Police Dept.18.322.23.921.3
37Arapahoe County Sheriff’s Office49.257.17.9216.1
38Sacramento County Sheriff’s Office16.118.72.5816
39Arlington Police Dept.50.355.34.979.88
40Virginia Beach Police Dept.17.819.31.58.44
41Shelby County(TN) Sheriff’s Office8.789.490.7098.08
42Suffolk County Police Dept.41.443.11.684.05
43Collier County Sheriff’s Office1515.30.2681.78
44Orange County(CA) Sheriff’s Dept.93.593.4-0.103-0.11
45Volusia County Sheriff’s Office41.537.6-3.88-9.36
46El Paso Police Dept.170152-18.1-10.6
47Kern County Sheriff’s Dept.5.094.47-0.621-12.2
48Lee County(FL) Sheriff’s Office2118.3-2.74-13.1
49Tucson Police Dept.62.241.2-21.1-33.9
50Washoe County Sheriff’s Office29.818.7-11.1-37.3
51Adams County Sheriff’s Office35.420-15.3-43.3
52Travis County Sheriff’s Office49.626.6-23.1-46.4
53Pittsburgh Bureau of Police45.420.4-25-55.1
54East Baton Rouge Sheriff’s Office14.36.38-7.93-55.4
55New Castle County Police Dept.9.453.61-5.84-61.8
Table 7

Agencies (in the higher-use group) ranked by the increase in the received retweets per tweet before and after the killing.

#Agency nameAverage number of retweets received per tweet pre-killingAverage number of retweets received per tweet post-killingRaw changePercentage change
1Portland Police Dept.5.6375.7701245
2Seattle Police Dept.17138121710
3Wichita Police Dept.4.6919.114.4306
4Charlotte-Mecklenburg Police Dept.3.8915.411.5295
5San Diego Police Dept.7.8430.923294
6Tampa Police Dept.4.9419.114.2288
7Columbus Police Dept.5.5521.315.8284
8Sacramento Police Dept.4.2614.910.6249
9Alameda County Sheriff’s Office6.8622.916234
10New York Police Dept.26.688.361.7232
11Austin Police Dept.7.4324.617.2231
12Baltimore Police Dept.5.8717.511.7198
13Miami Police Dept.4.1912.28.03192
14Dallas Police Dept.6.7919.712.9191
15Milwaukee Police Dept.2.256.223.97176
16Aurora Police Dept.4.6412.57.88170
17Oklahoma City Police Dept.7.4119.812.4167
18Denver Police Dept.1.714.272.55149
19Hillsborough County Sheriff’s Office4.0810.16.04148
20Phoenix Police Dept.15.735.219.6125
21Chesterfield County Police Dept.2.34.872.56111
22Las Vegas Police Dept.24.248.324.199.7
23Fort Worth Police Dept.13.526.713.197.1
24Omaha Police Dept.2.95.482.5889
25Chicago Police Dept.19.636.316.784.9
26Fairfax County Police Dept.5.379.363.9974.2
27D.C. Metropolitan Police Dept.9.1515.86.6873
28Douglas County(CO) Sheriff’s Office4.998.623.6372.6
29Pinellas County Police Dept.3.025.122.169.7
30Bernalillo County Sheriff’s Dept.1.342.220.87965.7
31Boston Police Dept.15.225.29.9665.5
32Richland County Sheriff’s Dept.1117.86.8362.3
33Baltimore County Police Dept.4.937.892.9660.1
34Palm Beach County Sheriff’s Office16.625.68.9654
35Loudoun County Sheriff’s Office2.313.51.251.9
36Houston Police Dept.15.623.37.6448.8
37Los Angeles County Sheriff’s Dept.18.727.38.645.9
38Gwinnett County Police Dept.5.98.572.6745.3
39Memphis Police Dept.3.865.271.4236.7
40Montgomery County (TX) Sheriff’s Office1.381.830.44332
41Jacksonville Sheriff’s Office18.824.55.730.3
42Harris county Sheriff’s Office10.113.13.0330.1
43Pierce County Sheriff’s Dept.15.920.64.7429.9
44Jefferson County(CO) Sheriff’s Office7.029.072.0429.1
45Montgomery County(MD) Police Dept.10.8143.1228.8
46Kansas City Police Dept.18.323.55.2328.7
47Prince George’s County Police Dept.11.7142.3119.7
48Manatee County(FL) Sheriff’s Office2.663.150.49318.6
49Prince William County Police Dept.3.33.890.59418
50Jefferson County(AL) Sheriff’s Dept.5.296.080.79815.1
51Orange County(FL) Sheriff’s Office6.046.890.84914.1
52Washington County Sheriff’s Office9.8111.11.2612.9
53Raleigh Police Dept.8.288.480.1912.3
54San Diego County Sheriff’s Dept.1616.30.2861.79
55El Paso County Sheriff’s Office7.627.690.06190.812
56Bakersfield Police Dept.3.53.23-0.266-7.62
57Broward County Sheriff’s Office14.813.5-1.33-8.98
58Henrico County Police Dept.1.581.35-0.228-14.5
59Honolulu Police Dept.2.992.4-0.59-19.7
60Anne Arundel Police Dept.4.663.21-1.45-31.1
Table 8

Agencies (in the lower-use group) ranked by the increase in the received retweets per tweet before and after the killing.

#Agency nameAverage number of retweets received per tweet pre-killingAverage number of retweets received per tweet post-killingRaw changePercentage change
1Ventura County Sheriff’s Office2.8143.440.61447
2Louisville Metropolitan Police Dept.7.6266.358.6770
3Saint Paul Police Dept.648.542.5709
4St. Louis Police Dept.5.634539.4700
5Sacramento County Sheriff’s Office2.051412584
6Anaheim Police Dept.7.2736.629.4404
7Unified (Salt Lake, Utah) Police Dept.1.035.114.08397
8St. Louis County Police Dept.6.0528.522.5371
9Minneapolis Police Dept.20.192.372.2359
10Albuquerque Police Dept.9.3342.232.9353
11Tulsa Police Dept.14.865.450.6343
12Metropolitan Nashville Police Dept.21.789.667.8312
13San Jose Police Dept.8.1431.223.1284
14Stockton(CA) Police Dept.3.0311.58.48280
15Philadelphia Police Dept.14.452.337.9263
16Lexington Police Dept.4.0812.88.69213
17Detroit Police Dept.6.618.511.9180
18Cleveland Police Dept.3184.153.1171
19Oakland(CA) Police Dept.8.7323.614.9171
20Colorado Springs Police Dept.4.5211.97.36163
21Pima County Sheriff’s Dept.5.6413.47.72137
22Dekalb County Police Dept.7.1115.88.65122
23Atlanta Police Dept.3780.143116
24Hennepin County Sheriff’s Office3.467.484.02116
25Osceola County Sheriff’s Office1.292.751.46114
26Mesa Police Dept.10.121.611.5114
27Santa Clara County Sheriff’s Office4.9110.45.51112
28Howard County Police Dept.6.2412.96.69107
29San Antonio Police Dept.17.635.317.7100
30Arapahoe County Sheriff’s Office4.158.164.0296.9
31Seminole County Sheriff’s Office3.76.963.2688.2
32Santa Ana Police Dept.4.988.473.4970
33Virginia Beach Police Dept.3.636.142.5169.3
34Los Angeles Police Dept.8613750.859.1
35San Francisco Police Dept.11.6175.3946.3
36Franklin County Sheriff’s Office10.214.84.645.1
37El Paso Police Dept.35.851.215.443
38Corpus Christi Police Dept.6.739.142.4135.8
39Long Beach Police Dept.3.95.071.1730
40Shelby County(TN) Sheriff’s Office4.765.430.67914.3
41Pittsburgh Bureau of Police8.69.570.9711.3
42Suffolk County Police Dept.7.68.390.79210.4
43Volusia County Sheriff’s Office8.919.690.7858.81
44Collier County Sheriff’s Office3.844.10.2636.84
45Lee County(FL) Sheriff’s Office3.073.03-0.0438-1.42
46Kern County Sheriff’s Dept.0.9560.933-0.0227-2.38
47Arlington Police Dept.8.768.28-0.477-5.45
48Washoe County Sheriff’s Office4.884.41-0.462-9.48
49Orange County(CA) Sheriff’s Dept.16.414.6-1.74-10.6
50Tucson Police Dept.23.521-2.56-10.9
51Adams County Sheriff’s Office2.572.19-0.38-14.8
52Riverside(CA) Police Dept.10.88.79-1.99-18.5
53East Baton Rouge Sheriff’s Office2.441.75-0.685-28.1
54New Castle County Police Dept.2.761.26-1.5-54.3
55Travis County Sheriff’s Office10.84.38-6.48-59.7
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).
Table 9

Agencies (in the higher-use group) ranked by the increase in posting category 1 (civil unrest related) tweets before and after the killing.

#Agency nameTotal number of tweets pre-killingTotal number of tweets post-killingNumber of C1 tweets pre-killingNumber of C1 tweets post-killingPercentage of C1 tweets pre-killingPercentage of C1 tweets post-killingPercentage change
1Portland Police Dept.303900053500.5940.594
2Dallas Police Dept.425491019300.3930.393
3Seattle Police Dept.11722607900.350.35
4San Diego Police Dept.20019105700.2980.298
5Charlotte-Mecklenburg Police Dept.1953142890.01030.2830.273
6Raleigh Police Dept.1621859460.05560.2490.193
7Aurora Police Dept.1514755970.03310.2040.171
8Phoenix Police Dept.18317302700.1560.156
9Chicago Police Dept.16819002900.1530.153
10Tampa Police Dept.1109101300.1430.143
11Sacramento Police Dept.15211301300.1150.115
12Austin Police Dept.16623702700.1140.114
13Miami Police Dept.49426902900.1080.108
14Anne Arundel Police Dept.18913401400.1040.104
15Boston Police Dept.21322402300.1030.103
16Bakersfield Police Dept.13416001600.10.1
17Kansas City Police Dept.2694181370.003720.08850.0848
18Las Vegas Police Dept.107710600.08450.0845
19Alameda County Sheriff’s Office17916301200.07360.0736
20Fort Worth Police Dept.19315001100.07330.0733
21Broward County Sheriff’s Office15116701200.07190.0719
22Columbus Police Dept.29330502000.06560.0656
23Omaha Police Dept.21533502100.06270.0627
24Jacksonville Sheriff’s Office14216201000.06170.0617
25San Diego County Sheriff’s Dept.1391330800.06020.0602
26Hillsborough County Sheriff’s Office23326401500.05680.0568
27Oklahoma City Police Dept.17822301200.05380.0538
28El Paso County Sheriff’s Office1331190500.0420.042
29Houston Police Dept.4444774230.009010.04820.0392
30Los Angeles County Sheriff’s Dept.266211190.003760.04270.0389
31Milwaukee Police Dept.42480302900.03610.0361
32Prince William County Police Dept.25733701200.03560.0356
33Baltimore Police Dept.1612290800.03490.0349
34Gwinnett County Police Dept.1191560500.03210.0321
35Richland County Sheriff’s Dept.62339801200.03020.0302
36Palm Beach County Sheriff’s Office1642060600.02910.0291
37New York Police Dept.66342801200.0280.028
38Denver Police Dept.791121702200.01810.0181
39Montgomery County(MD) Police Dept.1772610400.01530.0153
40Chesterfield County Police Dept.118670100.01490.0149
41Jefferson County(AL) Sheriff’s Dept.1251370200.01460.0146
42D.C. Metropolitan Police Dept.778108801500.01380.0138
43Pierce County Sheriff’s Dept.153770100.0130.013
44Wichita Police Dept.164810100.01230.0123
45Harris county Sheriff’s Office2221920200.01040.0104
46Jefferson County(CO) Sheriff’s Office1212030200.009850.00985
47Fairfax County Police Dept.366318130.002730.009430.0067
48Baltimore County Police Dept.2181580100.006330.00633
49Memphis Police Dept.1181870100.005350.00535
50Honolulu Police Dept.1952150100.004650.00465
51Bernalillo County Sheriff’s Dept.2092190100.004570.00457
52Prince George’s County Police Dept.2182280100.004390.00439
53Orange County(FL) Sheriff’s Office57563811140.01910.02190.00281
54Douglas County(CO) Sheriff’s Office11711200000
55Henrico County Police Dept.14310800000
56Loudoun County Sheriff’s Office11412100000
57Manatee County(FL) Sheriff’s Office11612800000
58Montgomery County (TX) Sheriff’s Office12510400000
59Pinellas County Police Dept.2234100000
60Washington County Sheriff’s Office12615100000
Table 10

Agencies (in the lower-use group) ranked by the increase in posting category 1 (civil unrest related) tweets before and after the killing.

#Agency nameTotal number of tweets pre-killingTotal number of tweets post-killingNumber of C1 tweets pre-killingNumber of C1 tweets post-killingPercentage of C1 tweets pre-killingPercentage of C1 tweets post-killingPercentage change
1Cleveland Police Dept.187504700.6270.627
2Stockton(CA) Police Dept.355303300.6230.623
3Anaheim Police Dept.574702100.4470.447
4Tulsa Police Dept.4610104100.4060.406
5Oakland(CA) Police Dept.659502800.2950.295
6Louisville Metropolitan Police Dept.204101100.2680.268
7Albuquerque Police Dept.79491120.01270.2450.232
8Atlanta Police Dept.336901600.2320.232
9Metropolitan Nashville Police Dept.1051181260.009520.220.211
10Minneapolis Police Dept.194801000.2080.208
11Long Beach Police Dept.4123204600.1980.198
12Detroit Police Dept.427101400.1970.197
13Lexington Police Dept.387201400.1940.194
14Colorado Springs Police Dept.851181240.01180.2030.192
15Riverside(CA) Police Dept.315501000.1820.182
16Los Angeles Police Dept.891752350.02250.20.178
17Saint Paul Police Dept.3610501800.1710.171
18Pittsburgh Bureau of Police7912802000.1560.156
19Philadelphia Police Dept.6213002000.1540.154
20Unified (Salt Lake, Utah) Police Dept.33170200.1180.118
21Santa Clara County Sheriff’s Office31190200.1050.105
22St. Louis County Police Dept.939701000.1030.103
23San Francisco Police Dept.921010900.08910.0891
24San Jose Police Dept.19270200.07410.0741
25Franklin County Sheriff’s Office75700500.07140.0714
26San Antonio Police Dept.21360200.05560.0556
27Sacramento County Sheriff’s Office37200100.050.05
28Mesa Police Dept.101410200.04880.0488
29Virginia Beach Police Dept.41950400.04210.0421
30Howard County Police Dept.50300100.03330.0333
31Arlington Police Dept.881550500.03230.0323
32Washoe County Sheriff’s Office811310400.03050.0305
33El Paso Police Dept.61730200.02740.0274
34Tucson Police Dept.43370100.0270.027
35Corpus Christi Police Dept.45400100.0250.025
36Hennepin County Sheriff’s Office61400100.0250.025
37Suffolk County Police Dept.70430100.02330.0233
38St. Louis Police Dept.8190130.01230.03330.021
39Pima County Sheriff’s Dept.651700300.01760.0176
40Ventura County Sheriff’s Office781150200.01740.0174
41Santa Ana Police Dept.991200200.01670.0167
42Lee County(FL) Sheriff’s Office81660100.01520.0152
43Osceola County Sheriff’s Office70670100.01490.0149
44Arapahoe County Sheriff’s Office66720100.01390.0139
45Shelby County(TN) Sheriff’s Office43760100.01320.0132
46Adams County Sheriff’s Office9412700000
47Collier County Sheriff’s Office497800000
48Dekalb County Police Dept.697100000
49East Baton Rouge Sheriff’s Office622400000
50Kern County Sheriff’s Dept.917500000
51New Castle County Police Dept.574500000
52Seminole County Sheriff’s Office332300000
53Travis County Sheriff’s Office203200000
54Volusia County Sheriff’s Office9471210.02130.0141-0.00719
55Orange County(CA) Sheriff’s Dept.5687320.05360.023-0.0306
Table 11

Agencies (in the higher-use group) ranked by the increase in posting category 7 (community engagement and outreach) tweets before and after the killing.

#Agency nameTotal number of tweets pre-killingTotal number of tweets post-killingNumber of C7 tweets pre-killingNumber of C7 tweets post-killingPercentage of C7 tweets pre-killingPercentage of C7 tweets post-killingPercentage change
1New York Police Dept.6634281792050.270.4790.209
2Orange County(FL) Sheriff’s Office5756382753850.4780.6030.125
3Miami Police Dept.4942691631220.330.4540.124
4Pinellas County Police Dept.223411880.08070.1950.114
5Richland County Sheriff’s Dept.6233983782790.6070.7010.0943
6Harris county Sheriff’s Office22219277840.3470.4380.0907
7San Diego County Sheriff’s Dept.13913384890.6040.6690.0649
8Baltimore Police Dept.16122931550.1930.240.0476
9Washington County Sheriff’s Office12615160790.4760.5230.047
10Omaha Police Dept.2153351302150.6050.6420.0371
11Wichita Police Dept.1648170360.4270.4440.0176
12Broward County Sheriff’s Office1511671151300.7620.7780.0169
13D.C. Metropolitan Police Dept.77810881211740.1560.160.0044
14Denver Police Dept.791121738570.0480.0468-0.0012
15Montgomery County(MD) Police Dept.17726127390.1530.149-0.00312
16Memphis Police Dept.118187430.03390.016-0.0179
17Jefferson County(AL) Sheriff’s Dept.1251371051120.840.818-0.0225
18Gwinnett County Police Dept.11915641500.3450.321-0.024
19Austin Police Dept.16623739490.2350.207-0.0282
20Oklahoma City Police Dept.17822361700.3430.314-0.0288
21Alameda County Sheriff’s Office17916361500.3410.307-0.034
22Milwaukee Police Dept.42480347580.1110.0722-0.0386
23Honolulu Police Dept.19521548440.2460.205-0.0415
24Prince William County Police Dept.2573371271520.4940.451-0.0431
25Kansas City Police Dept.2694181151590.4280.38-0.0471
26Houston Police Dept.4444771251110.2820.233-0.0488
27Bernalillo County Sheriff’s Dept.20921966530.3160.242-0.0738
28Chicago Police Dept.1681901161170.690.616-0.0747
29Fort Worth Police Dept.19315083530.430.353-0.0767
30Charlotte-Mecklenburg Police Dept.19531468850.3490.271-0.078
31Bakersfield Police Dept.13416034270.2540.169-0.085
32Columbus Police Dept.29330593700.3170.23-0.0879
33Prince George’s County Police Dept.21822841220.1880.0965-0.0916
34Palm Beach County Sheriff’s Office1642061061140.6460.553-0.0929
35Manatee County(FL) Sheriff’s Office11612867620.5780.484-0.0932
36Jefferson County(CO) Sheriff’s Office12120355730.4550.36-0.0949
37Loudoun County Sheriff’s Office11412176660.6670.545-0.121
38Boston Police Dept.21322488650.4130.29-0.123
39Raleigh Police Dept.16218552360.3210.195-0.126
40Los Angeles County Sheriff’s Dept.266211132780.4960.37-0.127
41El Paso County Sheriff’s Office13311955340.4140.286-0.128
42Montgomery County (TX) Sheriff’s Office12510475490.60.471-0.129
43Seattle Police Dept.11722635370.2990.164-0.135
44Fairfax County Police Dept.366318121600.3310.189-0.142
45Aurora Police Dept.15147534350.2250.0737-0.151
46Douglas County(CO) Sheriff’s Office11711279550.6750.491-0.184
47Jacksonville Sheriff’s Office14216251270.3590.167-0.192
48Las Vegas Police Dept.1077163280.5890.394-0.194
49Chesterfield County Police Dept.1186769260.5850.388-0.197
50Anne Arundel Police Dept.189134111520.5870.388-0.199
51Tampa Police Dept.1109165350.5910.385-0.206
52Hillsborough County Sheriff’s Office2332641571220.6740.462-0.212
53Baltimore County Police Dept.218158100360.4590.228-0.231
54Portland Police Dept.3039001051000.3470.111-0.235
55San Diego Police Dept.200191130760.650.398-0.252
56Henrico County Police Dept.14310859150.4130.139-0.274
57Dallas Police Dept.4254912281230.5360.251-0.286
58Sacramento Police Dept.152113105430.6910.381-0.31
59Pierce County Sheriff’s Dept.15377112280.7320.364-0.368
60Phoenix Police Dept.183173137640.7490.37-0.379
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 5th in posting more tweets per day, 3rd in receiving more favorites per tweet, 4th in receiving more retweets per tweet, 5th in posting a higher percentage of civil unrest related tweets, and 30th 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 1st 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.
Table 13

Agencies (in the higher-use group) ranked by the five dimensions combined.

#Agency nameRank ARank BRank CRank DRank EAverage rankOverall rank
1Charlotte-Mecklenburg Police Dept.5345309.41
2Seattle Police Dept.42234310.82
3Portland Police Dept.21115411.83
4Austin Police Dept.126111219124
5Milwaukee Police Dept.3815312215.85
6Omaha Police Dept.815242310166
7Baltimore Police Dept.13201233817.27
8Oklahoma City Police Dept.181217272018.88
9Denver Police Dept.111818381419.89
10Aurora Police Dept.131167452010
11Alameda County Sheriff’s Office40139192120.411
12Columbus Police Dept.3397223220.612
13Miami Police Dept.57171313320.613
14Dallas Police Dept.22111425721.214
15D.C. Metropolitan Police Dept.141627421322.415
16San Diego Police Dept.435545522.416
17Chicago Police Dept.25292592823.217
18Tampa Police Dept.4546105123.218
19New York Police Dept.54141037123.219
20Wichita Police Dept.59103441125.420
21Gwinnett County Police Dept.172138341825.621
22Kansas City Police Dept.93446172526.222
23Memphis Police Dept.6253949162723
24Boston Police Dept.34223115382824
25Hillsborough County Sheriff’s Office261919265228.425
26Fort Worth Police Dept.472723202929.226
27Houston Police Dept.302636292629.427
28Phoenix Police Dept.39242086030.228
29Sacramento Police Dept.51238115830.229
30San Diego County Sheriff’s Dept.38325425731.230
31Pinellas County Police Dept.6072959431.831
32Jefferson County(AL) Sheriff’s Dept.24285041173232
33Prince William County Police Dept.164149322432.433
34Montgomery County(MD) Police Dept.105445391532.634
35Raleigh Police Dept.15535363933.235
36Richland County Sheriff’s Dept.55393235533.236
37Palm Beach County Sheriff’s Office214434363433.837
38Bakersfield Police Dept.20475616313438
39Las Vegas Police Dept.483522184834.239
40Orange County(FL) Sheriff’s Office27455153235.640
41Harris county Sheriff’s Office44424245635.841
42Jefferson County(CO) Sheriff’s Office74944463636.442
43Broward County Sheriff’s Office375757211236.843
44Jacksonville Sheriff’s Office23504124473744
45Bernalillo County Sheriff’s Dept.32553051273945
46Fairfax County Police Dept.423726474439.246
47Los Angeles County Sheriff’s Dept.494037304039.247
48Chesterfield County Police Dept.563021404939.248
49Douglas County(CO) Sheriff’s Office363328544639.449
50Washington County Sheriff’s Office19585260939.650
51Prince George’s County Police Dept.353647523340.651
52Honolulu Police Dept.294359502340.852
53Loudoun County Sheriff’s Office315235563742.253
54Manatee County(FL) Sheriff’s Office285148573543.854
55El Paso County Sheriff’s Office415655284144.255
56Baltimore County Police Dept.534633485346.656
57Montgomery County (TX) Sheriff’s Office464840584246.857
58Anne Arundel Police Dept.52596014504758
59Pierce County Sheriff’s Dept.583843435948.259
60Henrico County Police Dept.506058555655.860
Table 14

Agencies (in the lower-use group) ranked by the five dimensions combined.

#Agency nameRank ARank BRank CRank DRank EAverage rankOverall rank
1Saint Paul Police Dept.32317147.81
2Minneapolis Police Dept.549102410.42
3Atlanta Police Dept.732382212.63
4Louisville Metropolitan Police Dept.85264513.24
5Philadelphia Police Dept.9715191613.25
6San Jose Police Dept.19151324114.46
7Ventura County Sheriff’s Office241140714.67
8Tulsa Police Dept.10131144115.88
9Cleveland Police Dept.2121815417.49
10Unified (Salt Lake, Utah) Police Dept.536720818.810
11Pima County Sheriff’s Dept.4162139151911
12Lexington Police Dept.121016134719.612
13Stockton(CA) Police Dept.259142502013
14Metropolitan Nashville Police Dept.3114129392114
15Oakland(CA) Police Dept.26231953421.415
16Detroit Police Dept.172717123822.216
17Anaheim Police Dept.438635322.617
18Los Angeles Police Dept.11263416282318
19San Antonio Police Dept.132029263123.819
20St. Louis County Police Dept.35218223724.620
21Riverside(CA) Police Dept.142552152025.221
22Albuquerque Police Dept.49181074325.422
23Osceola County Sheriff’s Office37192543425.623
24Santa Clara County Sheriff’s Office51282721225.824
25St. Louis Police Dept.3411438482725
26Long Beach Police Dept.13139115527.426
27Colorado Springs Police Dept.272420145227.427
28Hennepin County Sheriff’s Office47292436327.828
29Virginia Beach Police Dept.64033293628.829
30San Francisco Police Dept.323335232529.630
31Arlington Police Dept.153947311729.831
32Sacramento County Sheriff’s Office52385272729.832
33Arapahoe County Sheriff’s Office3337304463033
34Howard County Police Dept.501728302630.234
35Franklin County Sheriff’s Office383036252330.435
36Dekalb County Police Dept.363422481330.636
37Santa Ana Police Dept.303232412932.837
38Collier County Sheriff’s Office2243444793338
39Pittsburgh Bureau of Police205341184034.439
40Suffolk County Police Dept.48424237534.840
41El Paso Police Dept.294637333235.441
42Washoe County Sheriff’s Office165048323335.842
43Shelby County(TN) Sheriff’s Office184140453535.843
44Orange County(CA) Sheriff’s Dept.234449551236.644
45Lee County(FL) Sheriff’s Office424845421137.645
46Mesa Police Dept.543526284938.446
47Corpus Christi Police Dept.393638354638.847
48Kern County Sheriff’s Dept.414746501038.848
49Adams County Sheriff’s Office28515146193949
50Seminole County Sheriff’s Office46223152443950
51Tucson Police Dept.40495034424351
52Volusia County Sheriff’s Office454543543043.452
53New Castle County Police Dept.445554511844.453
54Travis County Sheriff’s Office215255535146.454
55East Baton Rouge Sheriff’s Office555453492146.455

Discussion

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.

Conclusion

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.

A complete list of the 115 law enforcement agencies included in the study.

(DOCX) Click here for additional data file.

Detailed categorization scheme used in the study.

(DOCX) Click here for additional data file.

Random forest and multiclass boosted trees classifier.

(DOCX) Click here for additional data file.

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

(DOCX) Click here for additional data file.

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

(DOCX) Click here for additional data file.
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