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

1. INFORMATION EPIDEMICS
AND COLLECTIVE ACTION
re:publica conference 2012, 4 May, 10:30
Dmitry Paranyushkin
www.noduslabs.com

2. Watch
the video on
vimeo.com/2035117
SOCIAL NETWORK
Evolution
(visualization by Gephi - www.gephi.org)

3. S I R
S I S
S I R S
EPIDEMIC MODELS
S: Susceptible, I: Infected, R: Removed/Recovered
(Ball 1997; Newman 2002; Newman et al 2006; Watts 2002)

4. most “friends”
adopted a
trend, so the
blue node does
the same finally
LOCAL CONTAGION
Information Cascades: herd-like behavior, influenced by the others,
when “conversion threshold“ is exceeded (Watts 2002; Hui et al 2010; Young

5. Watch
the video on
vimeo.com/36958670
GLOBAL CONTAGION
Message = Virus

6. TYPES OF NETWORK
Scale-free - degrees distributed following power-law
(a few, but significant # of well-connected and disconnected)

7. TYPES OF NETWORK
Random - degrees distributed “normally” across the nodes
(most have an average number of connections)

8. TYPES OF NETWORK
Small world - tightly-knit loosely connected communities
with short distance between the nodes

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. * not too many!
2. RANDOM SHORTCUTS
Scale-free networks with shortcuts are better in propagating,
dense networks are better for cascades. (Kuperman 2001; Yan et al 2008)

11. 3. START WITH A GROUP
Rapid spread of disease within tightly connected communities
can lead to an epidemic outbreak even if the links are loose

12. WHY?
Because once the contagion is spread within the group, it will
spread across super-network to the other groups (Ball 1997).

13. Better than random nodes, but still not Optimal - leave the same number
perfect - immunize random groups of susceptibles in each group
STRATEGIES OF RESISTANCE
Leave the number of susceptibles the same in each group, thus
preventing the virus from spreading within and throughout.

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, while
belonging to one of them at every moment of time;

15. 4. FOCUS ON BROKERS
The nodes that connect different communities, are the best one
to target when spreading a message. (Stonedahl 2010; Freeman 1997)

16. Image: CC Laura Billings @ FlickR
5. MESSAGE = VIRUS
The message should have the capacity to replicate itself
across the network.

17. Watch
the video on
vimeo.com/33742762
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. RECONTEXTUALIZE
Acknowledge the mindset of the target group,
but bring in some novelty.

19. Against Putin Facebook group The viral message should imply
“against Putin”,
not “protect animal rights”
THE SAME PURPOSE
The message should reiterate the purpose that brings
the target network together.

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. RUSSIAN PROTEST
MOVEMENT
Facebook groups analysis

22. “Putin Must Leave” Facebook group
24 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. “Volunteer and Activists” Facebook group
24 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. 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. 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. INFORMATION EPIDEMICS
AND COLLECTIVE ACTION
Thank you!
More on www.noduslabs.com -
Contact: Dmitry Paranyushkin | dmitry@noduslabs.com
Twitter: @thisislikecom | Facebook: Nodus Labs