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Information Epidemics re:publica conference Berlin


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A presentation given at re:publica conference in Berlin in May 2012. More information on

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Information Epidemics re:publica conference Berlin

  1. 1. INFORMATION EPIDEMICSAND COLLECTIVE ACTION re:publica conference 2012, 4 May, 10:30 Dmitry Paranyushkin
  2. 2. Watch the video on NETWORK Evolution (visualization by Gephi -
  3. 3. S I R S I S S I R S EPIDEMIC MODELSS: Susceptible, I: Infected, R: Removed/Recovered (Ball 1997; Newman 2002; Newman et al 2006; Watts 2002)
  4. 4. most “friends” adopted a trend, so the blue node does the same finally LOCAL CONTAGIONInformation Cascades: herd-like behavior, influenced by the others,when “conversion threshold“ is exceeded (Watts 2002; Hui et al 2010; Young
  5. 5. Watch the video on CONTAGION Message = Virus
  6. 6. TYPES OF NETWORK Scale-free - degrees distributed following power-law(a few, but significant # of well-connected and disconnected)
  7. 7. TYPES OF NETWORKRandom - degrees distributed “normally” across the nodes (most have an average number of connections)
  8. 8. TYPES OF NETWORKSmall world - tightly-knit loosely connected communities with short distance between the nodes
  9. 9. no connections between the nodes many connections between the nodes= cascades not possible = cascades can occur 1. GIANT COMPONENT Most nodes must belong to the same component for the global epidemics to occur (Watts 2002; Newman et al 2006)
  10. 10. * not too many! 2. RANDOM SHORTCUTSScale-free networks with shortcuts are better in propagating,dense networks are better for cascades. (Kuperman 2001; Yan et al 2008)
  11. 11. 3. START WITH A GROUPRapid spread of disease within tightly connected communities can lead to an epidemic outbreak even if the links are loose
  12. 12. WHY?Because once the contagion is spread within the group, it will spread across super-network to the other groups (Ball 1997).
  13. 13. Better than random nodes, but still not Optimal - leave the same number perfect - immunize random groups of susceptibles in each group STRATEGIES OF RESISTANCELeave the number of susceptibles the same in each group, thus preventing the virus from spreading within and throughout.
  14. 14. POLYSINGULARITY• Belonging to several distinct communities at once;• Introducing a degree of randomness in one’s interactions;• Integrating periphery, expelling the hubs;• Maintaining an overview of the existing centers, whilebelonging to one of them at every moment of time;
  15. 15. 4. FOCUS ON BROKERSThe nodes that connect different communities, are the best one to target when spreading a message. (Stonedahl 2010; Freeman 1997)
  16. 16. Image: CC Laura Billings @ FlickR 5. MESSAGE = VIRUSThe message should have the capacity to replicate itself across the network.
  17. 17. Watch the video on Rumours started on Twitter during the London riots were much more long-lived when started with a question.START WITH A QUESTION@someone “Is it true that Angela Merkel disappeared?” #weird #politics #germany #shithappens
  18. 18. RECONTEXTUALIZEAcknowledge the mindset of the target group, but bring in some novelty.
  19. 19. Against Putin Facebook group The viral message should imply “against Putin”, not “protect animal rights” THE SAME PURPOSEThe message should reiterate the purpose that brings the target network together.
  20. 20. 99%? 10% IS ENOUGH.Committed 10% can change the opinion of the majority as long as they persistently broadcast their message (Xie et al 2011)
  21. 21. RUSSIAN PROTEST MOVEMENT Facebook groups analysis
  22. 22. “Putin Must Leave” Facebook group24 December 2011 26 January 2012 • 9% more members (from 1809 to 1969), 15% more connections, • 58% of orphans (more than half of the people do not belong to the giant component), • relatively high network diameter (11) and average path: 3.7 (stifles communication), • prominent community structure that didn’t change (allows diversity of opinion, but stifles sync) • comprised of highly politically engaged groups: Kasparov’s followers and pro-Georgia activists • the group was busy adding new members, but there’s no change of dynamics within.
  23. 23. “Volunteer and Activists” Facebook group24 December 2011 26 January 2012 • 50% more members (290 to 411) and 120% more connections (695 to 1459) • lowest number of orphans – 36% of nodes are orphans (vs > 50% in other groups) • lower average path: 3.1 and lower diameter: 8 • communities are reconfigured, new centers of influence emerge, evolution of ideas • comprised of journalists and bloggers mainly (no political background)
  24. 24. SUCCESSFUL GROUPS• People talk to each other;• Periphery is integrated;• The hubs are leaving the center to form new groups;• Small number of “orphans”;• A unifying slogan is a call to action;
  25. 25. 1. Ensure Giant Component Exists(most of the people should be connected to each other, bring the “loners” in)2. Make Random Shortcuts between communities(communication outside of one’s community, diversity of links)3. Focus on Densely Connected Homogeneous Groups(better the more densely connected ones, 10% can be enough)4. Target Information Brokers(people who connect different communities together)5. Message = Virus(the message should have the capacity to replicate itself) SUMMARY Polysingularity of Information Epidemics
  26. 26. INFORMATION EPIDEMICSAND COLLECTIVE ACTION Thank you! More on -Contact: Dmitry Paranyushkin | Twitter: @thisislikecom | Facebook: Nodus Labs