This paper presents a case study on the use of sources by National Public Radio's Andy Carvin on Twitter during key periods of the 2011 Tunisian and Egyptian uprisings. Carvin, a social media strategist at NPR in the US, emerged as a key broker of information on Twitter during the Arab Spring.1 Through Twitter, Carvin would often link to images from demonstrators, curate a range of discussion and opinion about events, and frequently ask his followers (then about 50,000 strong) to help him make sense of the bits of information he encountered. This study examines the different actor types on the social media platform to reveal patterns of sourcing of information used by Carvin in order to further an understanding of how sourcing is evolving in an era of networked digital media—a space that, by its nature, allows for new research possibilities in tracking the influence of sources.
The interplay between journalists and sources is a significant factor in affecting what and who makes the news. Sources help to shape how events and issues are reported, influencing the public's understanding of the world. Studies on journalistic practices have highlighted key challenges in news routines, including a limited diversity of news sources and a reliance on those with institutional power, such as government officials, police officers or business leaders. The open nature of social media technologies could, in theory, foster greater pluralism in media discourse by providing channels for a greater number and diversity of news sources.
The availability of the messages sent by Andy Carvin on Twitter offers an opportunity to analyze his choice of sources on the Arab Spring, investigate the dynamics of discourse across institutional and alternative sources, and chart the predominance of voices on Twitter. This case study, built on a quantitative content analysis of his most frequently cited sources, provides insight into the process through which Carvin, as a member of the professional news media, negotiates information gathering and dissemination in this emerging social environment.
The Gatekeeping of News Sources
News sources are a critical element in the practice of journalism as it shapes from whom journalists get their information and what type of information they obtain (Carlson, 2009; Gans, 1979). Sourcing involves making decisions on who is included or excluded as an actor in the media. The sources cited in the media do more than denote events and issues. They ascribe meaning to events, shaping public perception and understanding. Studies into the production of news have shown that journalists seek to cite sources considered authoritative as they hold certain credentials in society (Ericson, Baranek, & Chan, 1989; Gans, 1979; Tuchman, 1978). These credentials stem from bodies holding positions of power, such as government or police, or representing significant segments of society, such as in business. Numerous studies have identified how government officials dominate sources (Brown, Bybee, Wearden, & Straughan, 1987; Sigal, 1973). Hall, Critcher, Jefferson, Clarke, & Roberts (1978) argue that elite sources are at the top of a hierarchy of credibility, and as a result, are primary definers who shape the news agenda and interpretative approach used by journalists. For Hall et al., the deadlines of news production and the professional commitment to impartiality and objectivity “combine to produce a systematically structured over-accessing to the media of those in powerful and privileged institutional positions” (1978, p. 58). Not only do nonelite sources make up a small minority of news sources, Ericson et al. argue they are used to inspire “fear and loathing” (1989, p. 1), reinforcing the authority of elites.
The use of elite sources by journalists further enhances the credibility of these sources. As Tuchman (1978, p. 210) notes, “by identifying centralized sources of information as legitimated social institutions, news organizations and newsworkers wed themselves to specific beats and bureaus. Those sites are then objectified as the appropriate sites at which information should be gathered.” The hierarchy of sources is replicated in alternative media, where a counterelite of source types “preserves the dominant model of sourcing in its assumptions about power, legitimacy and authoritativeness” (Atton & Wickenden, 2005, p. 357).
News practices reinforce what Becker defines as a hierarchy of credibility, where elites are presumed to have greater authority in defining “the way things really are” (1967, p. 241). Reporters develop routines to manage organizational limits and maximize efficiency (Gans, 1979; Tuchman, 1978). Journalists are expected to have a range of sources, yet come across operational impediments, including the geographic and social proximity of the source. Recent developments, such as the acceleration of the news cycle and the corresponding shortening of the publication cycle, have affected sourcing, with greater reliance on secondhand sources, such as news agency content or already published news stories (Boczkowski, 2010; Thurman & Myllylahti, 2009). Shrewd sources understand the limitations facing journalists and employ tactics to satisfy a reporter's need for information, hence increasing their chances of being cited. Gans (1979) describes the process as a tug-of-war between sources seeking to shape the content and direction of news, and journalists striving to obtain the details needed.
The credibility, or perceived credibility, of a source is a key determinant in the tug-of-war (Gans, 1979; Reich, 2011). While source type and affiliation affect how journalists assign credibility, operational limitations mean reporters develop ongoing relationships with sources. The more familiar journalists are with a source, the more likely they are to be considered credible. Engagement influences credibility and the likelihood of being used as a source. As Gans notes, “those they talk with frequently can be evaluated over time, which is another reason why story selectors prefer regular sources” (1979, pp. 129–130). In his study on sourcing and credibility, Reich (2011) found that journalists tended to depend almost exclusively on a core set of sources who had proved their trustworthiness in the past.
The selection of news sources, therefore, is an essential form of gatekeeping—the process through which journalists filter vast quantities of information to distill a narrow set of news reports for a given day (Shoemaker, 1991). The gatekeeping metaphor (White, 1950) has formed the theoretical basis for a wide range of mass communication scholarship, including many contemporary accounts of journalists' efforts to “guard open gates” (Singer et al., 2011) as news organizations increasingly engage participatory forms of news (Lewis, Kaufhold, & Lasorsa, 2010). In their seminal meta-analysis, Shoemaker and Vos (2009) propose that scholars examine the influences shaping gatekeeping at five levels of analysis: individual (e.g., personal background), routines (e.g., work patterns), organizational (e.g., media ownership), social institutional (e.g., extraorganizational forces such as public relations), and social system (e.g., ideology) (cf., Shoemaker & Reese, 1996). Moreover, Shoemaker and Vos suggest that a revised version of the gatekeeping model should give primacy not only to journalists (media channel) and their information (source channel) but should acknowledge the growing impact of user-driven information (audience channel) in shaping the media and source channels (see Figure 9.1 on p. 125). Additionally, Shoemaker and Vos contend that research should better account for the agency of individual gatekeepers, given that “the sociological turn in gatekeeping studies has left Mr. Gates as a minor character in the selection of news” (p. 134). This study attempts to address this concern and build upon their framework by (1) examining an individual gatekeeper whose agency is manifest in his publishing to Twitter without oversight from senior editors; (2) simultaneously addressing the social institutional level of influence from sources; and (3) exploring the extent to which journalists operating on social media may perform their gatekeeping function differently in relation to traditional or nontraditional types of sources.
Journalistic Sourcing and the Social Web
Web 2.0 technologies, often referred to as social media, offer broad opportunities for individuals to participate in the observation, filtering, distribution and interpretation of news. The negotiation between journalism and social media as structuring and/or shaping technology is a key point for understanding its role in influencing established norms, practices and routines. Social media allow for new relations that potentially disrupt hierarchical structures and erode the traditional distinction between the producer and consumer of news and information.
Services like Twitter facilitate the instant, digital dissemination and reception of short fragments of data from sources both inside and outside the framework of established journalism. The free service has grown as a network for real-time news and information since its creation in 2006, shaping how news is gathered, distributed, and received (Bruno, 2011; Hermida, 2010; Lasorsa, Lewis, & Holton, 2012; Newman, 2009). In its short lifespan, Twitter has attracted attention for its role in the reporting of major events, such as the terrorist attacks in Mumbai in November 2008, the protests following the Iranian election in June 2009, the earthquake in Haiti in 2010, and uprisings in Middle East (Bruno, 2011; Kwak, Lee, Park, & Moon, 2010).
Twitter describes itself as “a real-time information network that connects you to the latest information about what you find interesting” (Twitter, n.d.). By March 2012, it reported 140 million active users and 340 daily million messages (Twitter, 2012). Hermida (2010) has described the flows of news and information on Twitter as ambient journalism. Ambient journalism frames Twitter as a social awareness system that delivers a fragmented mix of information, enlightenment, entertainment, and engagement from a range of sources. In certain types of situations, Twitter users take on the role of social sensors of the news (Sakaki, Okazaki, & Matsuo, 2010), with the network serving a channel for breaking news alerts and subsequently for a stream of real-time data as events unfold.
As a result, Twitter has been promptly adopted in newsrooms as a mechanism for user-generated content, often filling the news vacuum that can follow the immediate aftermath of a breaking news event by sourcing eyewitness accounts, photos, and video from social media. This has given rise to the role of the journalist as curator who filters, selects and contextualizes copious amounts of real-time information on the fly (Bruno, 2011; Newman, 2009). The role of the journalist is reframed as a professional who “lays bare the manner through which a news story is constructed, as fragments of information are contested, denied or verified” (Hermida, 2012, p. 8). The technical architecture of Twitter presents distinct research opportunities to study the relationship between the journalist and sources, offering insights into the engagement with sources and the subsequent broadcast of information from these sources. The interactions between a journalist and a source are traditionally hidden from public view, making it difficult to assess whom a journalist has engaged with in the process of collecting information. Research on sourcing focuses on who is quoted by journalists as this can be measured by counting the number of citations in a news article or broadcast. However, the interactions between a journalist and a source are captured by the @mentions mechanisms on Twitter, revealing how a reporter engages with sources to gain information, background, and context. The sources cited are captured by the retweet mechanism, when a journalist broadcasts a message from a source.
Networked and distributed social media platforms potentially expand the range of actors involved in the construction of the news. Yet studies indicate that the ability of media audiences to participate in the processes of news production within professional publications has been severely circumscribed (Lasorsa et al., 2012; Lewis, 2012; Singer et al., 2011). Bruno's study of the coverage of three major news outlets of the 2010 Haiti earthquake suggests an opportunistic model at play, rather than a desire to represent a broad spectrum of voices. Bruno found a significant reliance of social media content by the BBC, The Guardian, and CNN in the first 24 hours of the natural disaster. But the use of social media content fell dramatically once the BBC and CNN had their own teams in Haiti. Bruno concluded that only “The Guardian seems to have embraced an editorial policy more open and consistent with regard to the diversity of online voices” (2011, p. 63).
Social media are attractive to activists as they can offer alternative platforms for public communication that bypass the gatekeeping of traditional media (Bruns, 2008). In the coverage of protest movements, the sourcing practices of the mainstream media shape the nature and tone of coverage. Journalists rely on institutional actors perceived as authoritative sources, such as police and officials, marginalizing alternative voices that are seen as deviant (Bennett, 1988; Hall et al., 1978). In their study on social media during the G20 protests in Toronto in 2010, Poell and Borra (2011) suggested that Twitter held the most promise for crowdsourced alternative reporting. However, they noted that the reporting was led by a small number of users who had emerged as an elite set of voices through the practice of retweeting. Moreover, Poell and Borra noted that the narrative on social media mirrored mainstream reporting on the violence during the protests as though activists focused on reports of violence by the police, rather than protesters.
Emerging research suggests that social media, and more specifically Twitter, provides a platform for the coconstruction of news by journalists and activists. In a study of tweets during the Tunisian and Egyptian uprisings, Lotan et al. (2011) found that both journalists and activists were key information sources. Activists were the top type of source cited on Twitter for Tunisia, whereas journalists became the main type of source for Egypt. The findings suggest that activists filled a news vacuum in Tunisia, a traditionally unreported country, as the protests unfolded and the international media started to play more attention. Egypt, in contrast, has tended to be better covered in the mainstream media in the past, and the protests garnered greater attention as they followed the ones in Tunisia.
Other studies of the protests that reshaped the Middle East in 2011 have highlighted how social media can give voice to a set of alternative sources. In their study of tweets using the #Egypt hashtag, Papacharissi and de Fatima Oliveira (2012) found that the more prominent voices on the Egyptian uprising belonged to elite news organizations and specific individuals. They found that, together with mainstream media journalists, there was a parallel and significant set of voices consisting of bloggers, activists and intellectuals involved in advocacy. This alternative set of elite voices was crowdsourced through the mechanisms of social media “that reward those more involved in mobilization, and the reporting and curating of information, online and offline,” (2012, p. 14). Papacharissi and de Fatima Oliveira suggest that the stream of news on Twitter combined news, opinion and emotion, pointing to a mix of old and newer news values.
The Case of Andy Carvin
To examine journalistic sourcing dynamics in a fluid news space like Twitter, and in particular how these dynamics played out in the Arab Spring, we have chosen to study Carvin's work at the height of the Tunisian and Egyptian uprisings. His coverage on Twitter—spanning upwards of 16 hours a day, 7 days a week—featured hundreds of tweets per day (Farhi, 2011). As Carvin emerged as a central node in the information network on the Arab Spring, his peers took notice. Summing up the reaction in media coverage after Carvin was featured in The New York Times, the Guardian, and The Washington Post, the Columbia Journalism Review called Carvin's Twitter feed a “living, breathing real-time verification system” and a “must-read newswire” (Silverman, 2011, para. 1). His prominence on Twitter resulted in a 2012 Shorty Award, which recognizes the best producers of short-form content on social media (PRWeb, 2012).
The literature on journalism and sourcing, the emergence of social media, and the particular case of Andy Carvin raise significant questions. First, given how the choice of sources influence how events are reported, our research seeks to understand how certain actors gain more attention than others in the process of gathering and filtering news. Second, the transparency of digital networks, and Twitter in particular, facilitate the work of identifying how such sourcing occurs. Third, the unique context of Carvin's role may point to a new kind of journalistic style emerging in social spaces, where reporters rely on a potentially broader array of sources, from citizens to individual activists to institutional bodies. The first two items are addressed in the research questions that follow; the third is the focus of the Discussion section that follows our findings.
Our primary concern is the nature of Carvin's sources: the type of actors involved, and the prominence that certain actors achieve relative to others. This leads us to ask:
RQ1. What types of sources are most prominent in Carvin's coverage of the Egyptian and Tunisian revolutions?
Secondly, because the networked and public architecture of Twitter presents an opportunity to observe the online interactions between journalists and sources—e.g., @mentions as a form of engagement, and retweets as a form of broadcasting—we seek to investigate the nature of Carvin's sourcing activity, and assess how such activity is associated with source type prominence.
RQ2. How does the relative prominence of source types vary according to the sourcing practices that Carvin employed during these periods?
The data for this study came from a dataset, provided by Carvin and obtained from Twitter, that included all of Carvin's tweets—more than 60,000 of them—posted between December 1, 2010 and September 16, 2011. The researchers developed a computer program to parse this data and systematically categorize them based on several criteria (for details, see Lewis, Zamith, & Hermida, 2013).2 All of the tweets appearing between January 12 and January 19, and from January 24 to February 13, were subsequently isolated by the researchers. The first period covers the major portion of Tunisian demonstrations leading to the fall of President Ben Ali, and the second covers the Egyptian protests and subsequent resignation of President Hosni Mubarak. These choices of dates were made according to an analysis of news timelines for major events during the Arab Spring,3 and to correspond with similar time frames used in previous research of this kind (e.g., Lotan et al., 2011). Carvin tweeted a total of 411 times during the Tunisian time period, including in his tweets 191 unique sources. During the Egyptian time period, Carvin tweeted 5,290 times and included 1,156 unique sources in his tweets.
To create a comparable and sufficiently large, yet manageable, sample, the researchers opted to code all profiles that accounted for 0.09% or more of the retweeted sources or 0.25% or more of the non-retweeted sources.4 This yielded 330 unique sources, with 190 sources appearing in the Egypt sample, 172 in the Tunisia sample, and 32 sources overlapping both samples. The Twitter profiles for these sources were then systematically downloaded by the researchers on December 6, 2011. A total of eight profiles could not be obtained since they had been either deleted or protected from public view, resulting in a final sample of 322 sources: 185 for Egypt and 168 for Tunisia, with 31 sources overlapping.
This study was primarily concerned with two key variables: (a) the type of interaction that occurred in a tweet and (b) the type of source being interacted with. To determine the type of interaction occurring in each of Carvin's tweets, a computer program was used to systematically ascertain whether tweets were broadcasting information or engaging sources. Tweets deemed to be broadcasting information were those that included a retweet, and were identified through the presence of the text “RT @” in the tweet, with the source being retweeted determined as the handle immediately adjacent to the expression. In cases where the text “RT @” appeared multiple times in one tweet, the first instance was given priority. Tweets that did not include the text “RT @” but did include a source (“@”) were deemed to represent engagement, with all sources appearing in the tweet listed as having been engaged by Carvin. Thus, retweets were classified as broadcasting and non-retweets as engaging.
The source type variable was initially assessed by two independent coders, who were blind to the research questions, and later re-evaluated by the researchers. All sources were coded using a customized electronic coding interface developed by one of the researchers. In this system, the source's Twitter profile page appeared adjacent to the electronic code sheet. This eliminated data entry error by automatically transferring entries into a relational database, removing the need for human intervention. It also helped reduce coder error by having options and categories presented as labels, with the system automatically converting selections into numerical values after each submission. Coders were instructed to rely primarily on the data from the source's stored profile, although they were also permitted to access external sources like the source's current Twitter profile, associated blogs and personal websites, and LinkedIn profile.
The source type classifications were adapted from Lotan et al. (2011). They included: affiliated activists, nonaffiliated activist, bloggers, bots, celebrities, digerati, mainstream media employees, mainstream media organizations, mainstream new media organizations, nonmedia activist organizations, nonmedia nonactivist organizations, political actors, researchers, and any other type of account. For a description of each source type, see Table 1.
|Activist (Affiliated)||Individuals who either self-identify as an activist or who appear to be tweeting purely about activist topics, and affiliate themselves with an advocacy group or organization.||@RachelPerrone|
|Activist (Non-Affiliated)||Individuals who either self-identify as an activist or who appear to be tweeting purely about activist topics, but do not affiliate themselves with an advocacy group or organization.||@Elazul|
|Blogger||Individuals who post regularly to an established blog, and who appear to identify as a blogger on Twitter.||@paulseaman|
|Bots||Accounts that appear to be an automated service tweeting consistent content, usually in extraordinary volumes.||@toptweets|
|Celebrity||Individuals who are famous for reasons unrelated to technology, politics, or activism.||@Alyssa_Milano|
|Digerati||Individuals who have worldwide influence in social media circles and are, thus, widely followed on Twitter.||@ev|
|Mainstream Media Employees||Individuals employed by MSM organizations, or who regularly work as freelancers for MSM organizations.||@camanpour|
|Mainstream Media Organization||News and media organizations that have both digital and non-digital outlets.||@NYTimes|
|Mainstream New Media Organization||Blogs, news portals, or journalistic entities that exist solely online.||@visionOntv|
|Non-Media Organization (Activist)||Groups, companies, or organizations that are not primarily news-oriented and openly advocate a point of view or support a cause.||@amnesty|
|Non-Media Organization (Non-Activist)||Groups, companies, or organizations that are not primarily news-oriented and do not openly advocate a point of view or support a cause.|
|Political Actor||Individuals who are known primarily for their relationship to government.||@jeanmarcayrault|
|Researcher||An individual who is affiliated with a university or think-tank and whose expertise seems to be focused on Middle East issues.||@jeffjarvis|
|Other||Accounts that do not clearly fit into any category.||@AngelinesMoncha|
To assess intercoder reliability, the independent coders double-coded 46 randomly selected sources (14.3% of the sample) that appeared within the dataset but outside of the sample. To determine reliability, the researchers used Scott's Pi, which corrects for chance agreement (Scott, 1955). The coefficient for the source type variable was .72, thereby exceeding the minimum bound of .70 suggested by Riffe, Lacy, and Fico (2005).
In light of the complexity of the source type variable—indeed, as in the Lotan et al. (2011) study, several sources were found to span several categorizations, presenting significant challenges—all profiles were subsequently reviewed by the researchers to ensure validity. When a researcher disagreed with a coder's classification—which occurred almost exclusively in the more ambiguous cases—that profile was reviewed by all three researchers simultaneously and recoded through consensus-building. A total of 60 sources (18.6%) were recoded in this manner.
Source Type Prominence
The relative prominence of source types (RQ1) was determined first by examining source representation in the sample (see Table 2). For instance, in the overall population of individual sources, mainstream media employees accounted for the largest group by far (26.7%). They were likewise the largest group by proportional representation within the Egypt (33.0%) and Tunisia (20.2%) subsamples. A closer look at proportional differences between countries reveals subtle changes as Carvin moved from the Tunisian revolution to the Egyptian revolution. For example, there was a substantial uptick in the representation of mainstream media employees and nonaffiliated activists, and a decline in the representation of digerati.
|Mainstream Media Employees||26.7%||33.0%||20.2%||29.4%||30.1%||23.2%|
|Mainstream Media Org.||4.3%||4.3%||4.8%||2.0%||1.8%||3.6%|
|Mainstream New Media Org.||1.2%||1.6%||.6%||1.2%||1.3%||.3%|
|Mainstream Media (group subtotal)||32.3%||38.9%||25.6%||32.6%||33.2%||27.1%|
|Non-Media Org (Non-Activist)||2.5%||.5%||4.8%||.5%||.1%||4.2%|
|Institutional Elites (group subtotal)||23.9%||19.3%||32.1%||11.7%||9.8%||29.8%|
|Non-Media Org (Activist)||1.9%||2.2%||1.2%||1.5%||1.6%||.6%|
|Alternative Voices (group subtotal)||26.4%||27.6%||23.2%||48.3%||50.1%||31.0%|
Proportional representation in the sample, however, is just one form of prominence; a more important measure is the relative frequency of tweet mentions given to source types (see Table 2). On this score, a different picture emerges: Compared to other individual source categories, nonaffiliated activists accounted for the greatest single share of tweet mentions, overall (35.3%) and for Egypt (37.5%). Meanwhile, mainstream media employees had the second-largest proportion for Egypt (30.1%) and the most for Tunisia (23.2%). Notably, digerati had a 16.3% share for Tunisia, but that fell to 3.8% in the Egypt sample.
A third step in this analysis of source type prominence was to organize the discrete source type categories originally deployed (see Table 1) into a more coherent, three-part scheme: Mainstream Media, Institutional Elites, and Alternative Voices (see Table 2). This arrangement allowed for a more focused comparison of the extent to which Carvin drew upon traditional sources for news (fellow journalists, researchers, institutions, and other elite actors) and nontraditional sources (activists and bloggers). This group-level comparison makes it clear that Alternative Voices enjoyed an outsized influence in Carvin's coverage; while they accounted for barely a quarter of his sources overall, they nonetheless received roughly half of all tweet mentions in the sample—far more than either Mainstream Media (32.6%) or Institutional Elites (11.7%).
Sourcing Practices and Prominence
The second research question sought to examine the nature of Carvin's sourcing practices—whether in the form of broadcasting (RTs) or engaging (non-RTs)—and assess how such activities are associated with source type prominence. The data were broken down by revolutionary period and by sourcing practice within each period (i.e., Egypt RTs, Egypt non-RTs, Tunisia RTs, Tunisia non-RTs). Sources in this context were considered at the level of the individual (single Twitter user) and the recoded three-part group structure noted above.
For prominence among individual sources, Tables 3-6 display a list of the top 25 sources for each of the four periods and sourcing practice classifications. Overall, there was little overlap across the lists,5 suggesting that, at least among go-to individuals, Carvin turned to a different set of sources for each revolutionary period—and even, it would appear, different leading sources.6 These lists also serve to illustrate the dramatic increase in Carvin's use of Twitter between the Tunisian and Egyptian periods, judging by the number of mentions required to crack the top 25 groups for each country. These tables also reveal the outsized influence of certain individuals, such as Sultan Al Qassemi (@sultanalqassemi), whose relative prominence among Egypt retweeted sources was unrivaled across the entire sample.
|1||@sultanalqassemi||Sultan Al Qassemi||Alternative Voices||161|
|2||@bencnn||Ben Wedeman||Mainstream Media||99|
|3||@monasosh||Mona Seif||Alternative Voices||92|
|4||@mosaaberizing||Mosa'ab Elshamy||Alternative Voices||87|
|5||@evanchill||Evan Hill||Mainstream Media||80|
|6||@dima_khatib||Dima Khatib||Alternative Voices||72|
|7||@riverdryfilm||Omar Robert Hamilton||Alternative Voices||66|
|8||@3arabawy||Hossam el-Hamalawy||Alternative Voices||65|
|9||@weddady||Nasser Weddady||Alternative Voices||64|
|10||@alaa||Alaa Abd El Fattah||Alternative Voices||63|
|11||@ramyyaacoub||Ramy Yaacoub||Institutional Elites||56|
|13||@ghonim||Wael Ghonim||Alternative Voices||52|
|14||@nickkristof||Nicholas Kristof||Mainstream Media||52|
|15||@sharifkouddous||Sharif Kouddous||Alternative Voices||51|
|16||@laraabcnews||Lara Setrakian||Mainstream Media||49|
|17||@monaeltahawy||Mona Eltahawy||Mainstream Media||48|
|18||@gsquare86||Gigi Ibrahim||Alternative Voices||47|
|20||@nadiae||Nadia El-Awady||Alternative Voices||42|
|21||@waelabbas||Wael Abbas||Alternative Voices||38|
|22||@bloggerseif||Ali Seif||Alternative Voices||37|
|23||@jan25voices||“Jan25 Voices”||Alternative Voices||36|
|24||@sandmonkey||Mahmoud Salem||Alternative Voices||35|
|25||@sherinet||Sherine Tadros||Mainstream Media||35|
|1||@ghonim||Wael Ghonim||Alternative Voices||26|
|2||@alaa||Alaa Abd El Fattah||Alternative Voices||19|
|3||@sultanalqassemi||Sultan Al Qassemi||Alternative Voices||19|
|4||@pubmedia||“#PubMedia Chat”||Mainstream Media||18|
|7||@evanchill||Evan Hill||Mainstream Media||17|
|8||@mathewi||Mathew Ingram||Mainstream Media||15|
|9||@webjournalist||Robert Hernandez||Institutional Elites||13|
|10||@weddady||Nasser Weddady||Alternative Voices||13|
|11||@mosaaberizing||Mosa'ab Elshamy||Alternative Voices||12|
|12||@3arabawy||Hossam el-Hamalawy||Alternative Voices||11|
|13||@dima_khatib||Dima Khatib||Alternative Voices||11|
|14||@monasosh||Mona Seif||Alternative Voices||10|
|15||@yayayarndiva||P. Mimi Poinsett||Other||10|
|16||@manal||Manal Hassan||Alternative Voices||9|
|17||@sandmonkey||Mahmoud Salem||Alternative Voices||9|
|18||@monaeltahawy||Mona Eltahawy||Mainstream Media||8|
|19||@ramyyaacoub||Ramy Yaacoub||Institutional Elites||8|
|20||@ajenglish||Al Jazeera English||Mainstream Media||7|
|21||@antderosa||Anthony De Rosa||Mainstream Media||7|
|22||@ivancnn||Ivan Watson||Mainstream Media||7|
|23||@jan25voices||“Jan25 Voices”||Alternative Voices||7|
|24||@jeffjarvis||Jeff Jarvis||Institutional Elites||7|
|25||@jilliancyork||Jillian C. York||Alternative Voices||7|
|1||@dima_khatib||Dima Khatib||Alternative Voices||6|
|2||@jrug||Jonathan Rugman||Mainstream Media||6|
|3||@nawaat||Nawaat de Tunisie||Alternative Voices||4|
|4||@sultanalqassemi||Sultan Al Qassemi||Alternative Voices||4|
|5||@achrisafis||Angelique Chrisafis||Mainstream Media||3|
|6||@brian_whit||Brian Whitaker||Mainstream Media||3|
|8||@ifikra||Sami Ben Gharbia||Alternative Voices||3|
|9||@lukebozier||Luke Bozier||Institutional Elites||3|
|10||@shadihamid||Shadi Hamid||Institutional Elites||3|
|11||@alanfisher||Alan Fisher||Mainstream Media||2|
|13||@edwebb||Ed Webb||Institutional Elites||2|
|15||@jeffjarvis||Jeff Jarvis||Institutional Elites||2|
|16||@jilliancyork||Jillian C. York||Alternative Voices||2|
|17||@mmm||Moh'd M. Meddah||Alternative Voices||2|
|18||@monaeltahawy||Mona Eltahawy||Mainstream Media||2|
|19||@niemanlab||Nieman Lab||Institutional Elites||2|
|20||@nprnews||“NPR News”||Mainstream Media||2|
|21||@sgardinier||Suzanne Gardinier||Alternative Voices||2|
|23||@techsoc||Zeynep Tufekci||Institutional Elites||2|
|24||@weddady||Nasser Weddady||Alternative Voices||2|
|1||@weddady||Nasser Weddady||Alternative Voices||11|
|2||@mathewi||Mathew Ingram||Mainstream Media|
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