Covering #SAE: A Mobile Reporting Class' Changing Patterns of Interaction on Twitter Over Time

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Covering #SAE: A Mobile Reporting Class’s Changing Patterns of Interaction on Twitter Over Time

Julie Jones1

AbstractThis study examined the social network that emerged on Twitter surrounding a mobile reporting class as they covered a national breaking news event. The work introduces pedagogical strategies that enhance students’ learning opportunities. Through NodeXL and social network cluster analysis, six groups emerged from the Twitter interactions tied to the class’s Twitter account, and four of the six were anchored by a student journalist in the class. By gathering their own social network around them, the students had the opportunity to experience what Hermida calls ambient journalism.

Keywordsmobile journalism, Twitter, ambient journalism, journalism education, breaking news

Introduction

Discussions regarding mobile journalism courses tend to focus on either technol-ogy (Jokela, Väätäjä, & Koponen, 2009; Quinn, 2009) or challenges to adopting a mobile centric course (Cochrane, Mulrennan, Sissons, Pamatatau, & Barnes, 2013). Less attention is given to where the students’ mobile content is published and with what outcome. In the spring of 2015, mobile journalism students at the University of Oklahoma covered a breaking news story on campus that quickly grew to national attention—the discovery of a cell phone video showing fraternity members chanting a racist song while on their way to a social event. News of the

1University of Oklahoma, Norman, USA

Corresponding Author:Julie Jones, University of Oklahoma, 395 W. Lindsey, Norman, OK 73019, USA. Email: [email protected]

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video first spread on social media on a Sunday afternoon in March and, by the evening, had gained attention from the university and the news media. Protests, peaceful marches, press conferences, and town hall meetings centered on the fra-ternity, and racial issues dominated campus life for days afterward. Mobile stu-dents covered these events from their phones and posted stories on two platforms—NewsCrowd, an online site developed for the journalism practicum class, and the Twitter account for the class, OU NewsCrowd. This study focused the Twitter side of the students’ coverage to examine how the class’s own social network evolved from Sunday night to Thursday morning when the story died down as spring break approached. Specifically, the study asked the following: How did the mobile class’s social connections on Twitter change over time as stu-dents continued to report on the story? A cluster analysis of the class’s Twitter interaction was performed via NodeXL, an open-source, donation based online social network analysis tool (Hansen, Shneiderman, & Smith, 2010). Four waves of data were analyzed that spread over the week as the story dominated campus life and activities. By examining changes in the social network patterns over time, this study provides a new perspective on the pedagogical practices and places those findings within the notion of ambient journalism (Hermida, 2010).

A Natural Fit: Mobile Devices, Breaking News, and Twitter

Although mobile reporting is consider a new “game-changer” for the field of journal-ism, the value of providing responsive, in-the-moment, location-based reporting online actually pre-dates the technology that popularized the term—the release of the first smartphone in 2007 (Westlund, 2012). For example, New Orleans citizens were able to provide more pertinent, geographically specific information via blog posts than the mainstream news media during the Katrina aftermath (Norris, 2006). Since then, citizens have “beat” journalists in posting vital information and images to the public straight from the front lines of breaking news events over and over again (Alan, 2007; Bivens, 2008; Quinn, 2009; Quinn & Quinn-Alan, 2006; Zdanowicz, 2014). Despite concerns that emphasizing mobile puts professional journalists at the level of amateurs, news organizations are developing their own mobile proprietary tools and, increasingly, seek employees with mobile skills (Aimonetti, 2011; Wenger, Owens, & Thompson, 2014). Meanwhile, journalism educators have experimented with mobile reporting at the level of gear, quality of the media produced, and Internet infrastructure (Jokela et al., 2009; Koponen & Väätäjä, 2009; Väätäja & Männistö, 2010). Cochrane et al. (2013) urge educators to not focus so much on the technology but, instead, on providing collaborative learning experiences that are possible because of mobile technology and social media spaces. This insight may be especially salient for journalism courses given that mobile devices and the social media platform Twitter are often considered uniquely suited to covering breaking news (Hermida, 2010; Java, Song, Finin, & Tseng, 2007).



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Twitter as the Location for Breaking News

On January 15, 2009, Jānis Kūnis stood on a ferry and posted his cell phone image of U.S. Airways plane, Flight 1549, downed in the Hudson River with its passengers flooding out to the awaiting boats (http://twitpic.com/135xa). To some, including the founders of Twitter, this moment and the mass attention the post drew were a defining one for the social media site (Langer, 2014). Kūnis’ post is an example of what Lasica (2003) calls “random acts of journalism.” Kūnis’ image also became widely shared and distributed rapidly illustrating what Hermida (2010) calls “ambi-ent journalism.” For its mobile users, Twitter is an always-ready, in-your-pocket tool that allows individuals a means of checking in on in-the-moment happenings and news shared among the person’s social connections. Furthermore, the 140 character limit makes Twitter a quick tool to create, read, and share content and information (Java et al., 2007). Mobile devices and Twitter appear to be perfect tools for break-ing news events for the public, for witnesses, and for journalists. However, to con-sider Twitter merely as a mobile tool negates the social connections underpinning users’ experiences.

Social Networks and Social Media Platforms

The mass popularity of social media platforms has provided mass communication scholars a unique perspective on how human behavior and discourse spread within social networks (Hansen et al., 2010). At its core, social networks analysis examines the pattern of social connections between people, groups, and/or organizations. Unlike biological or technical networks, human driven connections tend to cluster in highly connected groups (Newman & Park, 2003). Homophily, the notion that humans tend to form associations with others similar to one’s self, is thought to underpin social behavior online. For example, patterns within Twitter political dis-course have been found to cluster along conservative and liberal ideology (Himelboim, Mccreery, & Smith, 2013). These findings challenge the notion that online platforms are democratic and empowering. Social network patterns for news organizations also hint at a change in distribution. The old standards of success for newsrooms were based on how many people subscribed, read, or watched a news product. Distributing news via social media platforms is less a process of delivering a product down to audience and more a process of sharing content across groups interested in a story or event. In this way, the question becomes how journalists can reach across into clusters of users that may not have seen or shared their work oth-erwise. In short, where does the content go in a network and who spreads it? This study sought to examine that very question.

Before SAE: The Mobile Reporting Class Structure and Workflow

The mobile reporting class at University of Oklahoma is a journalism practicum offered to Gaylord College students every spring semester. This particular class was


http://twitpic.com/135xa



the fourth iteration of the course (offered since 2012), which was originally started through an Association for Education in Journalism and Mass Communication Knight News Challenge Bridge grant. This class consisted of nine students: six were journal-ism majors, two were broadcast media students, and one was a professional writing student who worked for the student newspaper. Included in the journalism cohort were two student editors; both had been mobile reporters the year before and had requested the job of editor then.

At the beginning of the semester, students established a professional Twitter account and became familiar with the mobile reporting kit (an Apple iPad Touch, ALM camera enclosure, a MKE 400 Sennheiser shotgun microphone, and a Mophie external bat-tery). Journalism standards centered on reporting, sourcing, verifying information, and writing; editing was stressed by the instructors. As to media, students were instructed on photography/video principles for smartphone devices as well as how to edited images and trim video through the Apple camera app. Apple’s iMovie was used to edit longer video stories. Although the students were encouraged to use the mobile kits, most preferred learning how to report from their own phones instead. Because the instructors built the course around the challenge report news in a professional manner with the devices “as close to pocket ready” as possible, students were allowed to use their own phones. Only one student, frustrated with video capturing on her Android phone, checked out the gear from the college’s inventory.

The class met once a week, and students were required to report news stories at least 4 times a week. They were also expected to respond quickly to editors’ requests and text messages during breaking news. The class used the GroupMe text messaging app as a communication tool between editors, students, and the instructors throughout the week. Racial issues had been an ongoing topic on campus because the advocacy group Unheard had presented the university with a list of grievances early in the semester (Bergum, 2015). Thus, the class deliberately focused on diversity events and issues on campus—including those sponsored by Unheard—even before news of the Sigma Alpha Epsilon (SAE) video broke. For example, one assignment early in the semester was to ask students of color whether they felt “heard” at OU and to post the videos to the class’s site NewsCrowd (www.thenewscrowd.com). Other stories cov-ered during the semester included student life events, cultural events, key speakers on campus (including a Tom Brokaw visit), and student opinions to current campus news.

Workflow for the class was different depending on the type of news event. For non-breaking news, students were instructed to post their text and media to the NewsCrowd site first and to message the editors when their story was uploaded. Once in the back end of the site, the editors would check the story for grammar, journalism errors in attribution or facts, publish the story, and then notify the student their story was up via the GroupMe account. At that point, students were required to Tweet a link to the story on NewsCrowd with a lead line via their professional account. Editors would retweet or quote the students’ post through the class’s Twitter account—OU NewsCrowd (see Figure 1 for example). With breaking news or live events, students posted to Twitter first and, when they could, posted their video clips and longer stories to the NewsCrowd site. Again, editors would retweet the students’


www.thenewscrowd.com


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post under the OU NewsCrowd account. Conceptually, then, the two different work-flow structures stressed either quality and depth of reporting (website first) or timeli-ness (Twitter first) depending on what kind of news event was being covered. The class was graded on a pass/fail basis, and no extra credit was given. Student editors were given independent study credit. No student failed the class.

Figure 1. Comparison of posts from mobile reporter’s professional accounts to the class’s account in Twitter.Note. At the top, screen grab of reporting on a philanthropy event on campus (SoonerThon). Reporter used his professional Twitter account to publish story. At the bottom, mobile editor’s two tweets regarding this story; first a promotional tweet before SoonerThon begins and a retweet of reporter’s post on the event. All three tweets were posted hours before the SAE chant was first captured via cell phone. SAE = Sigma Alpha Epsilon.




Covering #SAE: Word Spreads of a Racist Video

On the evening of Saturday, March 7, 2015, fraternity members from SAE were taking a bus ride to a social with their dates. While en route, the group chanted a song with racial slurs (the n-word) and references to the lynching of Black men. A cell phone video of the chant was shared on Snapchat—a social media platform designed to wipe messages off devices and servers up shortly after being sent. In this case, though, someone saw the post, recorded the video on their own device, and then shared it on social media. By early evening on Sunday, March 8, the video was a quickly evolving news story. The campus newspaper was first to report on news of the video via Twitter and the student website. Just as quickly, the national organization closed the universi-ty’s SAE chapter and Unheard announced it was organizing a protest for early Monday morning (Glenza, 2015). All of these actions—along with a statement from OU President Boren—were posted on Twitter. The hashtags #SAE and #SAEhatesme began to trend nationally on Twitter. After an impromptu call out on Twitter, a little more than 60 students and university employees gathered on campus to express their shock, anger, and to call for inclusiveness. Over the next few days, protests on campus were frequent and spontaneous while the news side of the story progressed; the two students seen in the video were identified and expelled, Boren held news conferences and a campus wide meeting with all fraternity members, a town hall meeting on racial issues was held at the business college, and national press landed on campus to cover the controversy. By early Thursday morning on March 12, news and events surround-ing the SAE video were in decline as the impending spring break drew near.

The class responded nearly as quickly as other media. The weekend editor had alerted everyone as to the video soon after the newspaper began reporting. Early reporting through the class’s Twitter account (OU NewsCrowd) was mainly verifying and retweeting information dug up elsewhere. The second student editor, working that night for the student newscast, pulled soundbites from an interview with a key official within the Black student association. Because he was tied to broadcast duties, the weekend editor wrote his story and posted the video clip to both NewsCrowd and Twitter. Three mobile reporters and the weekend editor covered the midnight gather-ing, and one reporter worked on SAE’s history with racial issues national wide. Others prepared to cover the early morning shift and the Unheard march. During the week, students and editors missed classes to keep reporting as scheduled and unscheduled events arose. When nothing was going on, students gathered soundbites across campus on how the events had changed individual’s perspective on racial issues at OU. This study examined the social network patterns that emerged from during the week from the class’s Twitter handle—OU NewsCrowd.

Specifically, the study asked the following: How did the mobile class’s social con-nections on Twitter change over time as students continued to report on the story? The class adopted a number of social media strategies at the beginning of the semester. As discussed, the students reported from their own Twitter accounts only mentioning the class’s account in their post. That way, the class’s Twitter handle appeared to be more active than if students were all posted under one account. By using their own accounts,



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students brought their own social connections into the class’s Twitter presence and formed connections over the semester with sources and people they met while report-ing. Next, students were encouraged to gather and use Twitter handles of the people they reported on or photographed. Both strategies were intended to increase both the OU NewsCrowd and the students’ presence on Twitter. The OU NewsCrowd account had only 330 followers before SAE news broke.

Method

Data Collection and Time Frame

The focus of analysis used for this study was the pattern of connections between tweets that mentioned OU NewsCrowd (in the text or by retweeting the OU NewsCrowd content). Data collection occurred at the end of the semester. Although the students were not aware that their Twitter connections would be analyzed for this study, they were instructed at the first of the semester that their work as mobile journalists would be public and accessible by anyone. No direct messages or any other private conversa-tion between Twitter account users was collected. This method of gathering the social network connections between public Twitter users and/or content has been used else-where (see Hansen et al., 2010; Himelboim et al., 2013).

NodeXL, an open-source social network software tool, was used to gather data in four time waves (8 a.m. EST on Monday, March 9; Tuesday, March 10; Wednesday, March 11; and Thursday, March 12). The keyword used to collect these data was the class’s Twitter account name—OU NewsCrowd. Only retweets and tweets that men-tion OU NewsCrowd were used for analysis. Thus, the social connections are between Twitter accounts (both organizations and individuals) that used OU NewsCrowd somewhere in the 140-character message. Because NodeXL includes time of post as metadata, analysis was originally categorized in five waves: the class’s social network Saturday before SAE broke, Monday morning at 12:01 a.m. CST, and then 12:01 a.m. to 12:00 a.m. on Tuesday, Wednesday, and Thursday. However, little changed in the network between Wednesday and Thursday. Thus, the findings include four time peri-ods: Saturday before SAE (Wave 1), through to Monday 12:01 a.m. (Wave 2), through to Tuesday 12:01 a.m. (Wave 3), and through to Thursday 12:01 a.m. (Wave 4). The data collection yielded 1,183 interactions between 340 Twitter accounts.

Findings

On Saturday, March 7, two students and the weekend editor were working two news stories: a campus wide, Greek life sponsored community service project for the city of Norman and a social justice symposium sponsored by the Women’s Outreach Center. The social network surrounding the class’s Twitter account was, at this time, sparse (see Figure 2).

Two clusters surrounded the two reporters working then (Groups 1, 2) and the edi-tor (Group 5) on duty. The class’s Twitter account lands between the two (Group 4).




Figure 3. Mobile class’s Twitter social network midnight after #SAE video news breaks.Note. SAE = Sigma Alpha Epsilon.

At the very end of Sunday night, mobile reporting students had been reporting on the SAE story for an hour and half through background stories, reactions from the leaders of Black student organizations—including Unheard—and through retweets of key information during the night, for example, public statements from university administration, the national SAE organization shutting the chapter down, and mem-bers leaving the SAE house. The class’s social network on Twitter increases at this time as well (see Figure 3). At this time, a group starts to cluster around the campus newspaper and its reporters (Group 3). Both student editors began to report themselves from the field as well as directing the student reporters and aggregating key informa-tion they could glean from social media and official OU sources. In the network, the student editor who was also working for the broadcast newsroom begins to appear in Group 1. On the edge of the network, a cluster begins to grow around the weekend editor that connects to the class’s account but not to the others. At this time, announce-ment of the midnight gathering has been reported, but the actual event had not yet begun.

The social network continued to increase in the next 24 hr as students covered the midnight gathering, the early morning march, impromptu protests, and reaction across campus (see Figure 4). In the network, a sixth group emerges at the fringe. At the core of this group are two students—both Black women—who were photographed by one

Figure 2. Mobile class’s Twitter social network an hour before #SAE video news broke.Note. Dots represent Twitter accounts (users) and lines represent interaction (e.g., retweet, mention, or quote). SAE = Sigma Alpha Epsilon.



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of the mobile reporters during the march. When the reporter posted the image, she added each woman’s Twitter handle in the post. From this, a small interaction emerged as the women retweet the post out to their social network (see Figure 4).

There were few changes in the social network in the next 24 hr. Students continued to report and post stories, but they did not grow many new connections in the network. Thus, the next figure represents the Twitter connections gathered early Thursday morning (see Figure 5). Interaction continues to increase across all groups including the two women whose Twitter handles were gathered at the protest (Group 6). Of par-ticular interest, though, is the increased interaction surrounding the student newspaper group (Group 3). Although this might have been due to the offline connects the jour-nalism students had with the paper’s newsroom (one even reporting for them at the same time), further analysis shows that one newspaper photojournalist is at the core of the clusters as he began to mention the OU NewsCrowd while covering a town hall meeting on racial issues held Wednesday night at the business college.

To better understand the characteristics of the six sub groups in the network, the top word pairs for each were gathered in NodeXL. In Group 1, the second mobile editor and RT (to designate retweet) were the top pairing; in Group 2, one of the students reporting on Saturday before the SAE video broke and RT were the top pairing; in Group 3, the student newspaper’s photojournalist and RT were the top pairing; in Group 4, the other

Figure 4. Mobile class’s Twitter social network midnight one day after #SAE breaks.Note. SAE = Sigma Alpha Epsilon.

Figure 5. Mobile class’s Twitter social network on the morning of March 12th, three days after #SAE breaks.Note. SAE = Sigma Alpha Epsilon.




reporter working on Saturday and RT were the top pairing; in Group 5, the editor work-ing Saturday before SAE broke and RT were the top pairing; in Group 6, the twitter handles for the two students photographed were the top pairings. The class’s twitter handle was the most frequently used word for all the groups except Group 3. Because this group was centered on the student newspaper and because OU NewsCrowd was not the most frequent word used in this cluster of tweets, Group 3 can be considered the only cluster that grew organically from the news event. In other words, this was cluster of interactions that came from the reputation OU NewsCrowd had gained with other journalists on campus rather than the connections students made directly with others through their Twitter retweets or personally through their reporting.

Discussion

Breaking news events present student journalists with a unique opportunity to report side-by-side with professional journalists under “real world” conditions. For this mobile class, covering the SAE controversy was no different. Starting on Sunday night, eight students—armed with only their own cell phones—put sleep and classes on the backburner to report on the ever evolving series of events centered on racial issues, student rights, and Greek life on campus. This study examined the Twitter social network that emerged from their work as a means of understanding not just what they produced but how others interacted with their Twitter content. The pattern that emerged is somewhat expected given how the class was structured. All semester long, students were instructed to use their own professional accounts when posting on Twitter but to mention the class’s handle when posting their work. Interestingly, though, the clusters that emerged were anchored by individual students rather than the class overall. These findings suggest that the strategy allowed the students not only the opportunity to connect with others but also—for at least three of them—the chance to grow their own, unique social network. In addition, one cluster—tied to the campus paper and centered on one photojournalist’s inclusion of OU NewsCrowd in his reporting—grew not out of individual connections but, rather, from other journalists on campus watching the mobile class’s work overall. Having students use their own accounts may have helped “spread the word” of what the class was accomplishing that week. This is logical given that these students share social connections inherently anyway. The mobile reporters are classmates, coworkers, and friends with the students working in the paper’s newsroom. That they would be watching each other work is not unex-pected; that they would start retweet or mention the “competition” in their own tweets is more surprising.

Certain limitations, of course, apply to this work. The data are presented only at the descriptive level, and the findings are not generalizable beyond the SAE case. Furthermore, given that some consider social network analysis reductive (Newman, 2010), future work should include interviews or content analysis to illustrate a richer picture of the Twitter interactions and the benefits to students. However, the study introduces a new approach to understand pedagogical strategies and their benefits for a mobile reporting class.



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Mobile devices and social media platforms are powerful partners. Increasingly, both the public and journalists turn to Twitter as an awareness tool during breaking news events. The SAE story is prime example of what Hermida (2010) calls ambient journalism. Although the cell phone video was posted on a platform that many con-sider secure and fleeting, in less than 24 hr after riding that bus, the racist lyrics chanted by the fraternity brothers (and their dates) were widely shared and trending nationally on social media venues. Within hours, the university’s SAE chapter was closed, and the campus community sought ways to connect and express a collective sense of out-rage and sorrow. By instructing students to use their own Twitter accounts as their point of distribution, mobile classes can leverage each student’s personal networks to gain exposure for the class’s work. More importantly, though, by placing each student ahead of the class’s brand, journalism professors can provide their students the experi-ence of reporting in an ambient journalism paradigm.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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Author Biography

Julie Jones is associate professor at the University of Oklahoma where she teaches multimedia and mobile journalism. She has teaching awards from the International Communication Association, Kappa Theta Alpha, and is the 2015 recipient of the Joseph Costa award, named for the founder of the nearly 70-year-old National Press Photographers’ Association.


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Covering #SAE: A Mobile Reporting Class' Changing Patterns of Interaction on Twitter Over Time

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