Contrasting Protest and Mundanity: Centralization & Cohesion in Opposition Communication Networks /...

8/12/2019 Contrasting Protest and Mundanity: Centralization & Cohesion in Opposition Communication Networks / .

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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

-

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

[email protected]

Contrasting Protest and Mundanity: Centralization & Cohesion in Opposition Communication Networks /...

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