Online clustering, fear and uncertainty in Egypt’s transition

Online clustering, fear and uncertainty in Egypt’s transition

  • Marc Lynch (webpage),
  • Deen Freelon (webpage) associate professor in the School of Communication at American University in Washington, DC. My primary research interests lie in the changing relationships between technology and politics, and encompass the study of weblogs, online forums, social media, and other forms of interactive media with political applications. Collecting and analyzing large amounts of such data (i.e. millions of tweets, Facebook wall posts, etc.) require methods drawn from the fields of computer science and information science, which I am helping to adapt to the long-standing interests of political communication research.
  • Sean Aday (From GWU) focuses on the intersection of the press, politics, and public opinion, especially in relation to war and foreign policy. He has published widely on subjects ranging from the effects of watching local television news to coverage of Elizabeth Dole’s presidential run to media coverage of the wars in Iraq and Afghanistan.Before entering academia, Dr. Aday served as a general assignment reporter for the Kansas City Star in Kansas City, MO; the Milwaukee Journal in Milwaukee, WI; and the Greenville News in Greenville, SC. He graduated from the Medill School of Journalism at Northwestern University in 1990.
  • …research has demonstrated the role played by social media in overcoming the transaction costs associated with organizing collective action against authoritarian regimes, in temporarily empowering activists against state violence, in transmitting images and ideas to the international media, and in intensifying the dynamics of social mobilization.
    • There is some kind of relationship between frictionlessness and credibility. Disbelief is a form of friction that needs to be overcome.
  • We argue that social media tends to exacerbate and intensify those factors which make failure more likely than in comparable cases which did not feature high levels of social media usage. Social media promotes the clustering of individuals into communities of the likeminded, and that these clusters have distinctly damaging implications during uncertain transitions.
    • I would add “as designed”, but uncertainty sets up an entirely different dynamic, which I doubt the designers took into account.
  • Users within these clusters tend to be exposed primarily to identity-confirming and enemy-denying information and rhetoric, which encourages the consolidation of in-group solidarity and out-group demonization. The speed, intensity, and intimacy of social media tends to exacerbate polarization during moments of crisis, and then to entrench very different narratives about those events in the aftermath.
  • Egypt was one of the first attempted democratic transitions since the widespread adoption of social media, and was one of the textbook cases for the internet’s effects on political mobilization. It is therefore significant that its society and politics became deeply polarized, protests continued in new forms, violence spiralled, a series of democratic elections were conducted, and ultimately a military coup ended the democratic transition.
    • Is this an example of a runaway polarization hitting a limit? Limits don’t have to be obviously self-destructive. They can be a threshold that causes the power structure to shift, or reactionary effects to manifest.
    • Also, this makes me think that this could be a recognizable trajectory across behavior space. LIke an H-R diagram hrdiagram1
      • And speaking of HR-diagrams, this is a great example of a behavior map. I think I would even contend that a map can be defined as a diagram that supports the plotting of trajectories
  • social media has distinctive effects on the flow of political information that makes such failures more likely by driving inter-group differences and intensifying inter-group fears. Provocative information spreads first through the clusters of affected communities, leading to divergent understandings of the situation at critical junctures. Social media clustering lends itself well to dehumanization of the other, by reinforcing both in-group solidarity and out-group demonization
    • There should be a heading and a velocity across some dimensions if this is true.
  • Social Identity Theory – provides grounding for antibelief and other flocking characteristics
  • Social media tends to radically accelerate and intensify the public perception of these events, with the intimacy of social networks and the potency of videos and images heightening their societal impact. Information flows unevenly, however, with each cluster presenting its own narrative of events.
    • Narrative is important here. Plots have trajectories, and the endpoint is greatly affected by the beginning
  • Prior, “Media and Political Polarization
    Arceneaux, Johnson, and Murphy, “Polarized Political Communication
    Conover et al., “Political Polarization on Twitter” <– looks very interesting
    Siegel, “Social Networks and the Mass Media.”
  • Information flows differently and has different resonance during the intense uncertainty of political transitions from authoritarian regimes, particularly where the mass media is itself highly partisan and politicized. [p 5]
    • Is this akin to weather?
  • Rumours and perceived outrage spread extremely quickly through trusted networks
    • Low friction pathways through familiar belief space?
  • Fear and the Ruptured State: Reflections on Egypt after Mubarak [Ref 23]
  • Louvain Method for community detection [p 8]
  • A cluster of American right-wing media personalities also appeared occasionally, but had virtually no interaction with any of the Egyptian or Arabic clusters. [p 8]
    • Because they had a different orientation and path through the same space?
  • Polarity, Insularity, Proximity, and Churn: Polarity captures the degree to which politics had polarized along a single cleavage or retained multiple crosscutting cleavages. Insularity captures the extent to which clusters had become closed echo chambers of the like-minded. Proximity captures the extent to which clusters shared common content. Churn captures the extent to which individuals moved between clusters [p 9]
  • Our data show the disappearance over time of superclusters, defined as distinct clusters sharing at least 20% of their content [p 9]
  • We interpret the disappearance of superclusters as evidence of the consolidation of political blocs, with diversity and pluralism disappearing into larger blocs. Ideologically similar but politically competitive groups sorted themselves out over time: multiple Islamist clusters became a single Islamist cluster, multiple activist clusters became a single activist cluster, and so forth. This typically happens because a single cleavage takes precedence over the other issues which had previously differentiated groups: for instance, shared hostility to Islamist rule overwhelms disagreement over economic policy [p 9]
  • Less “sharing” would indicate greater distance between the clusters, [p 10]
    • What’s the distance? Awareness? Shared belief?
  • Churn in this paper is another way of stating diversity or exploratory activity
  • Cluster churn would be more likely during times of low polarization, since individuals would move more easily between communities. The higher the Jaccard coefficient, the less churn – and, we believe, greater polarization. [p 11]
    • If explorers are a subgroup, there should be some minimum churn
  • Perhaps unsurprisingly, the Muslim Brotherhood typically shows the lowest level of churn, with the highest proportions of returning members. The Couch Party, a less ideologically coherent cluster lacking any formal political organization, shows the highest degree of churn. [p 11]
    • From an explore/exploit perspective, this makes sense
  • EgyptExploreExploit Looking at this figure, The couch party looks different in a statistically significant way. Linear regression of A and MB would have a positive slope, and couch would be flat or slightly negative.  Percentage is 30% for couch, roughly
  • The images, videos, and rumours popular on social media can carry a visceral, emotional impact. [p 12]
    • This is a way of achieving dimension reduction / funneling. Mapping in sentiment space could make a lot of sense
  • …present the violence within highly specific narratives: activist videos usually showed peaceful protestors attacked by vicious Islamist mobs, while Islamist videos often showed activists attacking Islamist buses and buildings or extreme behaviour by their adversaries. The violent images and videos powerfully reinforced each side’s identity narratives… [p 13]
  • This article has highlighted the effects of social media on existential uncertainty and fear, and its effects on accelerating the breakdown of revolutionary unity into polarized conflict along a single cleavage [p 15]
    • Or how dimension reduction using emotion enables polarization
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