Networked framing and networked gatekeeping on #Egypt
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This document discusses a study on broadcasting and listening practices on Twitter during the Egyptian protests in 2011. It examines how networked gatekeeping and framing occurred through prominent users and hashtags. The researchers analyzed over 1.5 million tweets to understand how gatekeeping and framing were negotiated through conversational markers like retweets, mentions, and hashtags. They also looked at how affect, ambience, and conversational practices created an always-on environment that sustained the movement. The study explores how gatekeeping and framing were crowdsourced and networked through Twitter to give prominence to certain actors, problem definitions, and interpretations during the real-world events in Egypt.
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Networked framing and networked gatekeeping on #Egypt
- 1. BROADCASTING AND LISTENING PRACTICES ON #EGYPT: NETWORKED GATEKEEPING AND FRAMING ON TWITTER Sharon Meraz, PhD Zizi Papacharissi @zizip Assistant Professor, Communication Professor and Head, Communication University of Illinois at Chicago University of Illinois at Chicago
- 2. premise • Twitter and news storytelling • Collectively prodused news feeds and the news economy • Twitter as alternative/primary channel for information
- 3. previous research • Twitter as news reporting mechanism • Established news values guide use of Twitter • News breaking/premediation/instantaneity • Homophily, peripheral awareness and ambient news environments, hybridity • Twitter as news sharing mechanism during uprisings • Electronic word of mouth • Broadcasting and ‘listening in’ on uprisings • Homophily and group identity +++JOC theme issue
- 4. research design • Networked Gatekeeping • Networked Framing RQ1: Who were the prominent users and how was their prominence negotiated across the different conversational markers? RQ2: To what extent did prominent users forge connections to other users based on the users’ levels of prominence across the different addressivity markers? RQ3: To what extent does the usage of hashtags reflect an organic level framing to the real world events occurring during the Egyptian protests? RQ4: What types of conversational practices support processes of gatekeeping and framing negotiation? • METHOD Frequency analysis (R), 1.5 mil multi-lingual tweets, network analysis (SQL queries), discourse analysis
- 5. 20000 40000 60000 80000 100000 120000 140000 160000 180000 0 1/24/2011 1/25/2011 1/26/2011 1/27/2011 1/28/2011 1/29/2011 1/30/2011 1/31/2011 2/1/2011 2/2/2011 2/3/2011 2/4/2011 2/5/2011 2/6/2011 2/7/2011 2/8/2011 2/9/2011 2/10/2011 2/11/2011 2/12/2011 2/13/2011 2/14/2011 2/15/2011 2/16/2011 2/17/2011 2/18/2011 2/19/2011 2/20/2011 2/21/2011 2/22/2011 2/23/2011 2/24/2011 @ RT VIA count dual processes of networked gatekeeping and framing
- 6. dual process of networked gatekeeping and framing networked framing networked gatekeeping RT Via @ Bencnn Youtube Ghonim Monaeltahawy AddThis Monaeltahawy Dima_Khatib Guardian AJEnglish AJEnglish Addthis Sandmonkey Cnnbrk Ajenglish Andersoncooper BorowitzReport Huffingtonpost Ghonim Ghonim Fran AJELive Sharifkouddous Washingtonpost Bencnn AymanM Telegraph 3arabawy AlArabiya_Eng AymanM CNN ArabRevolution Alyssa_Milano BarackObama TheAlexandrian Reuters Alaa NickKristof Nytimes Monasosh Marwame AndersonCooper Dima_Khatib AlMasryAlYoum_E AJEnglish AymanM JoeUnfiltered AlexMLeo Zeinobia RawyaRageh TIME Acarvin AJELive Arabist ElBaradei Democracynow FrankRG SultanAlQassemi SherineT Nobelegypt NickKristof
- 9. conversational affordances and practices • Affect and ambience • Conversational practices mix of news, opinion, emotion reflecting movement toward the not yet, retweets as conversational refrains/chorus, affective gestures support contagion and rhythm, state that conveys impression of constant movement • Always on environment with a life cycle and pulse of its own, sustaining movement even when nothing new is going on • Networked gatekeeping and framing • Conversational tendencies • Cosmopolitanism/fluency in (multi) cultural context • Directly conversational, become embedded via offline and online activities
- 10. Practices of broadcasting / listening / redacting • Networked Gatekeeping Process through which actors crowdsourced to prominence through the use of addressivity markers and conversational practices • Networked Framing Process through which a particular problem definition, causal interpretation, moral evaluation, and/or treatment recommendation attain prominence through crowdsourcing practices • Affect and ambience support always on space - electronic elsewheres - that treated this movement as a revolution well before it had actually become a revolution Thank you! @zizip uic.edu/~zizi
Editor's Notes
- As it emerged as key platform for newsstorytelling of the egyptian uprisings that led to regime reversal
- Research has shown that Twitter is quickly emerging as a medium for news storytelling, sometimes involving collaborative storywriting, more frequently involving collaborative filtering / curating of news2. Collectively prodused news feeds by citizens committing acts of journalism substitute or complement mainstream media coverage, especially during times economic constraints force media companies to curtail or cut down on international news bureaus3. At times when access to mainstream media is blocked, restricted, or otherwise controlled, twitter quickly emerges as …. (Iran, occupy, Arab Spring, Anti Glob movment)
- 1 – Delivers same news, over different platform - contributes/cultivates culture of instantaneity2. Who says what to whom – more important than that, who is able to listen, as platform affords visibility to little covered issues.- replies between like minded people strengthen group identity, replies between people who disagree strengthen in group and out group affiliation. (hybridity in power structures +routines) (local topics, endogenous categories foster greater social connectivity, group cohesion)
- Who said what to whom and howUsed gatekeeping for who said what to whom, and framing to focus on what and how
- Explain who is whoFraming: hashtag as organic frame – users select - topically frame, express solidarity: 2 dominant trends: something that is going on within Egypt but should have consequences beyond Egypt, and revolutionRQ1: Who were the prominent users and how was their prominence negotiated across the different conversational markers? Prominent users more likely to be independent journalists, activists, and mass media entitiesMass media entities were more likely to be prominent across via indicatorProminence did vary across conversational markers; yet, a few users were able to capture authoritative ranking across all indicators on a day by day basis (mention users such as Mona, Dima, Wael, Democracy Now journalists such as Andy Carvin, Ben Wederman from CNN, Al Jazeera English, and regular users such as Zenoibia). Can show table 2 for this part.RQ3: To what extent does the usage of hashtags reflect an organic level framing to the real world events occurring during the Egyptian protests?A series of hashtags emerged as contagious or sticky, suggesting an organic level of framing that arose to characterize or describe the revolution. These tended to be time related (25-Jan), place related (Egypt), and person centered (Mubarak). Framing by folksonomy and crowdsourcing (see table on hashtags)Hashtags represented events as they unfolded in Egypt (#Egypt, #tahrir, #mubarakHashtags captured the spread of the protests across the region to the Arab Spring (#sidibouzid to Tunesia, #Algeria, #Iran, #Libya, #Bahrain)
- Popular (retweeted) not necessarily the most valued – overall density of ties among core actors low - ties long, strength of weak ties – figure examines this moreExplain how this looks in the discourse analysis - prominent actors not talking amongst themselves, talking to the people --- figure 2 and dicourse analysis confirms thisFigUtilizinga smaller subsample of the top 100 prominent actors across each individual addressivity marker, social network analytic methodologies were employed to derive a series of network visualizations of these chief opinion leaders or influentials. Consolidating the top 100 prominent actors across each addressivity marker yielded 201 unique nodes or actors, with 91 actors copresent in more than one marker. Figure 1 provides a network visualization of the unique 201 nodes in all three connectivity scenarios. In the visualization, larger nodes represent those actors with high indegree connections (addressivity markers that point to them). The visualization is laid out by the graph theoretic layout of principle components and colored based on the cores of connectivity occurring in this network of 201 unique prominent nodes across the addessivity markers. In this scenario, red nodes represent those actors that are more strongly interconnected and connected as a whole within the network. Density (0.037) and general reciprocity measures (0.0890) among core prominent actors reveal a network with a low level of connectivity among prominent actors. Further inspection of the network visualization in Figure 1 results in some interesting conclusions about how the networked effect of the Twitter platform crowdsources individuals into significance. Elite mass media actors in the offline world were less able to transfer their prominence to other prominent actors. Disconnected individuals, termed isolates (nodes appearing on the left side with no ties or lines to other nodes), include such elite offline actors as Bloomberg News, The London Telegraph, the Jerusalem Post, and the London Review. Other connected elite nodes are part of a core of less connected individuals, and these nodes include such actors as the New York Times, CNN, the Washington Post, and NPR, or elite international news outlets like the Guardian or the BBC news. Regional specific news outlets like Al Jazeera English are more highly connected than US centric media outlets. Even popular blogs like the Huffington Post, TechCrunch, and Global Voices gain less centrality among the top core of prominent actors. This data reveals that though many of these aforementioned nodes were popular in an overall sense in the network, the value of these nodes to more prominent nodes was less significant.ure 1
- Figure 2 visualizes this low level of interconnectivity: the red lines reveal reciprocal connections, which is confined to a core group of actors. This low degree of interconnectivity among all prominent actors suggests that overall prominence of the majority of these central actors was facilitated by the lower level linkages of the long tail of the Twittersphere. Dense interconnections among prominent actors exist among select nodes, with the majority of the prominent nodes disconnected or weakly connected to each other.What did these people do to merit these recognition, how did they talk to othersFigure 2RQ2: To what extent did prominent users forge connections to other users based on the users’ levels of prominence across the different addressivity markers?Prominent users were no more likely to link to themselves as opposed to linking to others (suggest usage of the twitter platform to engage)Yet, prominent users in each addressivity marker were more likely to link to other prominent users (with prominence defined as top 10%) Among the most influential base of prominent users (defined as top 100 users across each addressivity marker resulting in 200+ unique nodes), there was low density ((0.037) and reciprocity ((0.0890) measures, suggesting very few network connections among most prominent users (result indicates that the crowd plays a strong role in buoying up nodes to significance, a strong filtering role)Most prominent users (those with high degree and betweeness centrality) were more likely to be mass media journalists and activist and less likely to be general mass media twitter accountsYou can show the two network diagrams. One shows the division of the prominent nodes in clusters of connectivity (called kcores, first network diagram), the next shows the low levels of connectivity among prominent nodes (second network diagram). Basically these findings show that the crowd was responsible for enabling some prominent nodes to become prominent, and that among these most prominent nodes, traditional media twitter accounts was less valuable or influential
- that led to regime reversal. Affect and ambience helped sustain and drive the collective imagination of what might happen, before it happened