INTRODUCTION:
It was August 9th, 2014 when unarmed 19 year-old Michael Brown was fatally shot by police officer Darren Wilson in Ferguson, Missouri. This incident was immediately followed by unrest amongst the community members, creating protests that would eventually draw nationwide attention. The community waited patiently for the grand jury to decide whether or not Darren Wilson would be indicted on the charges of murder. During this time, the media and an assembly of journalists followed the story closely, using a variety of platforms (Facebook, Twitter, printed newspapers, etc.) to distribute relevant news. Because of its highly visible nature and networking ability, journalists turned to Twitter to circulate news to mass audiences, framing the story of Michael Brown’s death to the public through several different lenses. My research will closely analyze how journalists used the media, specifically Twitter, to portray law enforcement in the days immediately following Michael Brown’s death, as well as in the days after the grand jury released their decision not to indict police officer Darren Wilson.
LITERATURE REVIEW/THEORETICAL CONSTRUCT:
The events in Ferguson raised several questions regarding the relationship between the media and law enforcement. While in Ferguson, several journalists were arrested and detained for their activity during the protests. This showed a clear disregard for their occupation by law enforcement, preventing them from fulfilling their obligation to report on the events that occurred in Ferguson (Brauer and Lutton, 2014). At one point, President Obama stepped in and claimed, “Here in the United States of America, police should not be bullying or arresting journalists who are just trying to do their jobs and report to the American people, what they see on the ground” (Brauer and Lutton, 2014, pg14). Because of this, a court order was signed on August 15th, 2014 further distinguishing the journalists’ right to freedom of press, including the use of recording and photography equipment (Brauer and Lutton, 2014). Unfortunately, law enforcement ignored the journalists’ legal rights to be present during the unrest in Ferguson and continued to deter journalists from accomplishing their intended purpose of collecting and releasing information to the public. This strain may have given journalists due cause to criticize and negatively portray law enforcement in Ferguson.
The framing theory has also had a significant impact on the portrayal of law enforcement by journalists. According to Sarah Brown (2015), “Media framing is the manner in which information is presented to audiences at its most basic form” (pg115). Brown conducted a study using content analysis, comparing different media resources from the Rodney King beating and the Michael Brown shooting, to determine if and how news media sources have progressed in their coverage of racially sensitive stories. She claimed that media framing provides the public with an explanation of a series of events, allowing them to connect themes and make informed decisions. Brown (2015) argued that historically, stories and current events were gathered in bulk and then distributed in different platforms with a broad spectrum of perspectives, where contemporary news tends to be catered towards viewers’ desired content. The results of her study showed that wording, the frame of black hardship/black youth misfortune, and the frame of the black community/civil rights leaders’ versus authorities, typically portrayed law enforcement in a disapproving manner. For example, one article released on the Michael Brown shooting quoted the young victim’s father saying, “Ferguson police just executed my unarmed son” (Brown, 2015, pg118). By including this statement, the journalist frames the police as executioners, rather than protectors of the general public. In another instance, the articles regarding Michael Brown’s death included words such as “brutality,” “racial discrimination,” and “threat” (Brown, 2015). Brown’s study further concluded that images and broadcast media coverage also had a profound impact on the way police officers were portrayed in both the Rodney King and Michael Brown shooting. Ariaza et al (2016) claims that “visual framing analysis has taken on a life of its own as images have become central to studies that examine the larger messages conveyed by patterns of image use” (pg2). Often times, images have the ability to express things that may be difficult to express using words. This is relevant to my study because I analyzed how tweeted images portray law enforcement, as well as tweets with text.
It is also important to recognize the protest paradigm at work during the time in which the media and journalists were covering the Ferguson story. (Guszowski, 2015). The protest paradigm can be deconstructed into four different sections: (1) frames and narrative (2) reliance on official sources and official definitions (3) invocation of public opinion and (4) delegitimization, marginalization of protestors (Guszowski, 2015). Looking at social movements, the protest paradigm tends to ignore protestors’ issues and focuses instead on their appearance, which can be detrimental to the movement. Often times, this paradigm creates an image that frames the police against the protestors, which was a potential theme I was looking for within my data set. Guszowski (2015) also discusses how different news firms may frame a story in one way versus another due to political affiliation. For example, during the 1968 Democratic Convention protests in Chicago, The New York Times tended to criticize law enforcement, using spoken accounts from protestors in their stories.
METHODOLOGY:
The bulk of my research was conducted on Pulsar, “a social media monitoring and analysis tool that gives you instant access to online conversations” (Pulsar TRAC: User Guide 2016). This data set consists of 48,234 tweets, collecting tweets from 92 users, with 47 activists and 45 journalists. Because my study focused on the portrayal of police following the Michael Brown shooting as well as in the days after the final verdict was released, I chose to gather data from August 9th to August 13th and November 24th to November 27th. Within the August dates, I chose to begin the data search at 14:15pm on the afternoon of the 9th, as this seemed to be the time at which tweets regarding Michael Brown’s death began appearing and circulating. I closed the data search on the 13th at 14:15pm, as well. Though the first dates provide a span of four days, the second set of dates only expand over a three day period due to the fact that the data on Pulsar only goes as far as November 27th at 23:59pm. Therefore, the time period for the dates in November began at 20:00pm on the 24th, as this was the relative time at which the grand jury released its decision. My research relied solely on original tweets to ensure that I wasn’t analyzing repeated tweets, and this simply provided a way to wean out tweets that were not coming from a primary source. My results were further filtered by choosing the tag “Journalists,” which meant that I only viewed tweets that were posted by those users tagged as “Journalists.” The research was then again filtered through the use of keywords, specifically “cop” OR “police” OR “law enforcement,” as these words made it easier to discover what journalists were saying when discussing law enforcement personnel. Through these steps, August 9th to August 13th resulted in 192 tweets and November 24th to November 27th resulted in 275 tweets.
Using these results, I used ethnographic content analysis to categorize my tweets, seeking definitions and deeper meanings while reading. Ethnography typically refers to a “careful description, definition, and analysis of aspects of human interaction” (Schneider, 1987, pg24). Although I did not physically analyze human interaction, my analysis studied social interactions on Twitter. Ethnographic content analysis follows a four step process, which can be understood as: (1) sampling-data (2) collection-data (3) coding-data and (4) analysis-interpretation, which is seen in the steps I took during my research. I created two tags, “Amanda: Objective” and “Amanda: Affective” in order to categorize the tweets into two different groups. It is important to understand why these two tags were chosen before delving into the core of the results. The tag “objective” was given to tweets that presented factual details without added emotion or personal opinion. The tag “affective” was given to tweets that presented this added emotion or personal opinion. This study was particularly interesting to conduct, though, because there were several tweets I recognized as both objective and affective. The reasoning behind this came from Sarah Brown’s (2015) research on media framing and how factors such as wording and images can take an objective post or story and make it possible for the viewer to recognize it as affective. This concept is made clear in the presentation and discussion of the findings. Both qualitative and quantitative research was used to analyze the collected tweets.
FINDINGS AND DISCUSSION:
Between the dates of August 9th to August 13th, there were 192 tweets posted by journalists that contained information relevant to “cops,” “police,” or “law enforcement.” Within these results, it was determined that 186 tweet were objective, 45 were affective, and 40 tweets fell into the category of both. Searching the dates of November 24th to November 27th resulted in a total of 275 tweets from journalists who mentioned one of the three keywords. Of these tweets, 261 were categorized as objective, 38 were found to be affective, and 32 of these tweets were tagged as both. The number of tagged objective tweets far outnumbers those tagged as affective, possibly due to the fact that journalists’ supposed purpose is to circulate factual news. Image 1 is an example of a tweet that was categorized as objective throughout the tagging process. The tweet represented by Image 1 was tagged as objective because it presents data in a way that doesn’t frame the police as murderers; the viewer simply knows that a 19-year old was shot by a police officer. It was quite rare that a tweet was tagged only as affective, which could have been due to the fact that the posts were not from activists reflecting on current events, but journalists attempting to circulate news. Image 2 is a tweet that was tagged as affective. As shown in Image 2, this user is using Twitter to express his feelings toward the prosecutor who failed to bring the police officer who killed Michael Brown to court. This tweet shows clear emotion and opinion from the user, categorizing it as affective. There were several tweets that were tagged as objective and affective, which can be rationalized using a number of different explanations. For example, Image 3 is a tweet with an image showing the police using pepper spray in an attempt to remove the seated protestors from the middle of the street. The reasoning behind tagging this tweet both as objective and affective is due to the statement being objective, factual data, but also affective because the photograph presents a negative image of the police, spraying non-violent protestors with pepper spray. In this image, the protestors are framed as the innocent victims, where the police appear to be the antagonists. This was a reoccurring theme in many of the photos posted on Twitter by journalists. Other journalists posted photographs that presented a situation of Police vs. Protestor, instead of protecting the public and working collectively to create a safe and welcoming community for all. Image 4 shows a clear divide between the protestors and police, which could be understood as rivalry and tension by users viewing this post. In other cases, certain tweets were tagged as both objective and affective due to the wording of the post. Image 5 presents information worded in a way that frames Darren Wilson as someone who tends to be involved in situations revolving around violence. If the viewer did not take the time to read the full description below the tweet or open the full story in another tab, the original tweet could negatively affected the way in which the user viewed Darren Wilson. This was a reoccurring theme with the tweets that were tagged as both objective and affective.
LIMITATIONS:
Throughout my study, I came across several factors that presented limitations on my research and analysis. After filtering my sample in order to collect only original tweets, I noticed that there were still a few tweets that were retweets. Although this did not have a substantial effect on my analysis, it did alter the number of tweets I analyzed and tagged, as well as elongating the analyzation process. The data I analyzed was solely retrieved from Pulsar, which presented a number of limitations on my research. First, my study was restricted to the data set that was on Pulsar. Although Pulsar is a technologically advanced data collection site, it still presented technological difficulties throughout the process of my study. At one point in the research, I had to go back through the filtered sample and re-tag every tweet, as the tags had disappeared. Of course, the fact that I was the only researcher conducting this study presented limitations, as well. The tagging process was subject to which tags I believed were objective versus affective, presenting unintentional bias. It would have been beneficial to have the expertise of other sociology researchers to analyze the sample set with me. I also could have researched the political background of each journalists and the news firm who employed them, which could have given me a better understanding of why each journalists chose to frame law enforcement the way they did.
CONCLUSION/FUTURE RESEARCH:
Journalists have the ability to use platforms such as Twitter to portray law enforcement in a way that frames them as the public enemy. Though my research presented instances in which this was true, far more tweets from journalists remained objective, void of opinion or emotion. My research aligned well with Sarah Brown’s study on media coverage of the Rodney King incident and the Ferguson conflict, as the images on Twitter posted by journalists played a vital role in the portrayal of law enforcement. The research showed that very few journalists used Twitter to share personal feelings regarding what occurred the day of Michael Brown’s death and in the weeks of protest following. The stipulations of this study may make it difficult to replicate in the future, unless the researcher has access to a database such as Pulsar that provides the exact same data set. If given more time and a team of researchers, I may have analyzed all of the tweets posted by journalists from the day that Michael Brown was fatally shot to the day that the data set is cut off (November 27th). This would have given me a larger sample set to work with and potentially, the opportunity to see what journalists were saying about law enforcement when tension and unrest were at a lull. Over all, my research appeared to agree with already existing research, though the collection of my data was specific to the Pulsar platform and not produced through field work.
Works Cited
Araiza et al. (2016). Hands up, don’t shoot, whose side are you on? Journalists tweeting the Ferguson protests. Cultural Studies: Critical Methodologies. 1-8. Web.
Brauer, S.M. and Lutton, M. (2014). Ferguson: A fascination and troubling study of visual politics, race, the police, and the media. Dvafoto. 1-20. Web.
Brown, S. (2015). A framing analysis of media coverage of the Rodney King incident and Ferguson, Missouri, conflicts. The Elon Journal of Undergraduate Research in Communications. Vol. 6 (1). 114-124. Web.
Guszkowski, J. (2015). Framing Ferguson: A content analysis of St. Louis news media coverage of the Ferguson protests. Journalism Masters Project. 1-290. Web.
Schneider, A. (1987). Chapter 2. Ethnographic content analysis. Qualitative Media Analysis. 23-37. Web.
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