How does social media impact the perception of excessive use of force? Orr, T. Research Proposal March 3, 2015

Research Problem/Question There is no central database for record keeping of excessive force incidents (Johnson, Hoyer, & Heath, 2014). Researchers find it difficult to gather statistical data on the number of excessive force incidents (Johnson, Hoyer, & Heath, 2014). Research Question Has social media decreased the number of excessive use of force incidents? Does social media deter police officers from using excessive force? The research problem in this proposal discusses the fact that researchers have a hard time gathering data on excessive force because there isn’t a central database for record keeping exclusively on excessive force. Police reports and citizens complaints can be obtained through open record requests, but the reports don’t clearly state it was an excessive force incident. The research question for this proposal is, has social media decreased the number of excessive use of force incidents? I chose this question because there is no research related to police officers being deterred by social media. For instance, are they less likely to use force if they know they are being recorded.

Hypothesis Hypothesis: Social media has decreased the number of excessive force incidents that occur in the United States. Null hypothesis: Social media has no impact on the number of excessive force incidents that occur in the United States. The Hypothesis for this research proposal is… social media has decreased the number of excessive force incidents that occur in the U.S. This research is important because social media posts can be used as evidence against an officer. And we have seen in some cases where videos of police incidents make a difference in charging the officer, like with Rodney King, and in other cases it doesn’t make a difference, like with Eric Garner. May influence policy changes such as body cameras May influence citizen reactions to police activity

Literature Review What we know about excessive force Race of officer – no effect (Hassell & Archbold, 2010) Age of officer – younger more incidents, older less incidents (Hassell & Archbold, 2010) Education of officer- high school more incidents, bachelors degree less incidents (McElvain et al, 2008). Suspect resistance – more likely to use force (Stinson, 2015) What we don’t know The impact of social media on the perception of excessive force There has already been a lot of research conducted on excessive force. A few of the variables we looked at were race, age, and education of the officer, as well as resistance of the suspect. Research finds that….Race….Age…..Education….Suspect Resistance We found no research on the impact of social media on the perception of excessive force.

Methodological Plan Explanatory Study Mixed Methods Research will identify the causes and effects between social media and excessive use of force Mixed Methods Netnography Content analysis Time series design The methodological plan used for the research proposal is a three part mixed methods explanatory study consisting of a netnography, content analysis, and time series design.

Methodological Plan, cont. Netnography Research study focusing on online communities Identify widely shared social media posts related to excessive use of force. Application programming interface (API) U.S. Facebook and Twitter accounts 6.7 million shares A netnography is…. So the first step in the methodological plan is the identify widely shared social media posts related to excessive force We will do this by using an application programming interface to pull backend data from U.S. Facebook and Twitter Accounts We will be looking for social most posts that are tagged as excessive force or police brutality and have more than 6.7 million shares. That would equate to 10% of the U.S. population that has some type of social media account. Ok, so first we are pulling social media posts from Facebook and Twitter.

Methodological Plan, cont. Content Analysis Uses available data to measure variables and provide conclusions based on the finding Tie social media posts to police departments in the U.S. Collect data from police reports and citizen complaints Create a list of each police department that can be linked to the netnography data The second step is a content analysis. We will take the data collected from the netnography study and use it to tie those widely shared social media posts to specific police departments in the U.S. That way we can create a list of every police department in the U.S. that had an excessive force incident go viral on social media.

Methodological Plan, cont. Time Series Design Before and after observations Once we have a list of police department, the third step will be a time series design that will be used to analyze the number of excessive force police reports or citizen complaints that occurred five years before and five years after the social media post went viral. So each police department will have a separate time series study done to determine if the number of excessive force incidents decreased after they had an incident go viral on social media. It is also possible that the number of incidents could increase or remain the same. The graph above shows the anticipated findings for about 10 police departments. We anticipate that the findings would show a 10-15% decrease in the number excessive force incidents. So the blue line displays the number of excessive force incidents before social media While the green line displays the number of excessive force incidents after social media

Limitations Logistical Challenges: 6.7 million shares may be too high Problems linking social media post to police department Difficult to identify excessive force police reports and citizens complaints for time series design As with any research design there are some limitations. Some of the logistical challenges include…. 6.7 million shares may be too high to produce enough results We may have problem linking the social media post to specific police departments. We hope to use the geographical information of the poster to tie the cases to a local police department but that may not work with every post. Also, it may be difficult to gather police reports and citizen complaints for the time series design, because of the issue of police reports not being specifically marked as excessive force, so the researcher will need to study the wording of each report or complaint to determine if the record should be included

Limitations Design Limitations: Selection bias – high traction on social media may lead to only high profile cases Generalizability - findings will need to include several states to be generalizable to the U.S. Causality - intervening and confounding variables such as new laws being established, more funding for community officers, and additional funding for officer training Additional design limitations include selection bias because a high volume of shares on social media may lead us to only high profile excessive force cases. There may be an issue with generalizability if there are not enough incidents to apply the findings across the entire U.S. And there may be problems with causality because intervening and confounding variables can affect the research results. So if new laws were established related to excessive force at the same time the social media incident occurred we won’t know if the decrease in excessive force cases is due to the new law or if it is due to social media.

References Hassell, K. D., & Archbold, C. A. (2010). Widening the scope on complaints of police misconduct. Policing, 33(3), 473-489. doi:http://dx.doi.org/10.1108/13639511011066863. Johnson, K., Hoyer, M., & Heath, B. (2014, August 15). Local police kill 400 a year. USA TODAY. Retrieved from http://search.proquest.com/docview/1553432121?accountid=38769. McElvain, J. & Kposowa, A. (2008, April). Police Officer Characteristics and the Likelihood of Using Deadly Force. Criminal Justice and Behavior, 35, 505-521. doi:10.1177/0093854807313995. Stinson, P. (2015). Police Crime: The Criminal Behavior of Sworn Law Enforcement Officers. Sociology Compass, 7-8. John Wiley & Sons Ltd.