contrasting protest and mundanity: centralization & cohesion in opposition communication networks /...
TRANSCRIPT
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Social Networks & Social
MovementsTraditional Topics
Recruitment
Diffusion
Relationships between organizations
Protests
Crucial to social movement research
No network studies at protest sites
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How do we characterize
networks within a protest?
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Two Characteristics
Leadership
Solidarity
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LeadershipIncreases movement success and recruitment
(Ganz 2009; Lind & Stepan-Norris 2011)
Conflicting viewpoints
It's necessary (McCarthy & Zald 1977; Oliver et al. 1985)
Coordination and organizational skillsStart-up costs
Media work
It's avoided (e.g., Piven & Cloward 1977; Polletta 2005; Nepstad & Bob 2006)
Ideological reasons
Co-optation
Repression
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SolidarityTogetherness
Movements display "WUNC" (Tilly 2004)
Worthy, Unified, Numerous, Committed
Collective identity (Snow 2001)
a shared sense of one-ness or we-nessCommonalities & informal ties bound movement
(Diani & Bison 2004; Diani & Pilati 2011)
Yet...
Not a homogeneous "crowd" (McPhail 2006, 2008)
Patchwork gatherings (McPhail 2008)
Clustered: "withs" and "singles"
Groups defined by the foci of their interaction
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Brief Case BackgroundOrigins
Contested 2011 State Duma Election
4 December 2011
Turning point
6-7 May 2012 violence at protestPutin's presidency
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Data
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Underlying Assumptions
Protests occupy a specific location (Fillieule 2012)
A protest's beginning, middle, and end refer to occupationperiods.
Occupation affects the location's demographic and
communicative structure.
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Data CollectionCase selection: Moscow Opposition Protests
Demonstrations lead by opposition activists
Sanctioned and/or widely announced in news
Determine location, date, start and end times
Source and processTwitter: 140 character "micro-blog" updates
Available on desktop and mobile devices
"Following" = directed communication
Collect all updates from location during protest
Construct follower network
Repeat during same time and place one week later
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Date Time C Issue Type People Users Points Radius
12/6 12-4 23 General March 22k 345 4 1km
26/7 7-10 26.7 Prisoners Rally 800 117 1 1km
15/9 2-10 16.8 General March 14k 1204 7 .75-
1km
20/10 12-6 12.8 Elections Rally 600 317 1 1km
21/10 3-9 11.7 Elections Rally 600 166 1 1km
30/10 7-9 -0.8 Prisoners Rally 500 135 1 1km
15/12 3-
5:30
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14.2
Prisoners Gathering* 400 178 1 .5km
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June 12, 12-4pm (March)
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June 19, 12-4pm
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Methods
User differences
Network differences
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User DifferencesMeasurements
Hedge's g, standardized difference of means
Following, followers, lists, tweets, account age
Difference of proportions (Fisher's stabilization)
Proportion of Russian language users
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User DifferencesMeasurements
Combine Theta (g and expressed as Ti)
Combine p-values using Stouffer's method
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Network DifferencesMeasurements
Leadership measured by centralization
Closeness, out
Betweenness
Solidarity measured by cohesionStrong components (n)
k-core (median)
In
Out
Global, undirected transitivity (proportion)
"Clustering coefficient"
Meas(Protest) - Meas(Non-protest)
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Network DifferencesConditional Uniform Graph (CUG) tests
Create two random networks for each pairing
Base each upon characteristics of the observed networks
#Vertices & degree distribution
Randomly rewire 10 * #edges
Take measurements and subtract difference
Repeat 1000 times to generate null distribution
Combine
Z-scores: Mean across pairs, bootstrap distribution
p-values: Stouffer's method
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Findings
Network differences
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June 12, 2012. 12-4pm.
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July 26, 2012. 7-10pm.
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September 15, 2012. 2-10pm.
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October 20, 2012. 12-6pm.
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October 21, 2012. 3-9pm.
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October 30, 2012. 7-9pm.
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December 15, 2012.
3-5:30pm
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January 13, 2013. 1-4:30pm.
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March 2, 2013. 1-6pm.
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FindingsUsers
Protest users are more engaged with Twitter
More followers, following, lists, & tweets
No difference: adoption time, and language
Network visualizations
Many more people during protests
Greater density during protests
Network CUG tests
Leadership: closeness, but not betweenness
SolidarityMore components, k-cores out
Less k-cores in, transitivity
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ConclusionProtest brings more people, interactions to a locationLeadership through reach
Solidarity
Patchwork--many more clusters
Emphasis on sending, avoidance of receiving
Avoidance of redundant transitive communication
Limitations
Representation
Trade-offs when conditioning by degree
Future researchProximity effects
Expand study across differing political contexts
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Thank You!
Questions and comments?
Benjamin Lind