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Social media participation types:
Activity and degree distributionwithin online protest communities
Sofiya Dokuka
Department of Sociology, RSUHCenter for the Study of New Media and Society
sdokuka@nes.ru
www.newmediacenter.ru
Sunbelt XXXIII
May 23, 2013
Center for the Studyof New Media and
Society
mailto:sdokuka@nes.ruhttp://www.newmediacenter.ru/http://www.newmediacenter.ru/mailto:sdokuka@nes.ru7/28/2019 Sunbelt-Dokuka-v5.pptx
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Motivation
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Russians protest after the parliamentary elections in 2011
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Motivation
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Russians protest
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Motivation
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Russian Protest
One of the biggest meeting took part on Bolotnaya Square on the 10th of December in 2011.
Approximately 100 000 participants. (Government = 25,000; Media = 100,000; Opposition = 125,000)Sunbelt XXXIII
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Research problem
How to study the mechanism of protest recruitmentthrough social media?
Research goals
Discussion dynamics
General structure of protest communication
Formal structure of the protest communities and its
dynamics Types of participants in protest communities
Methodology for studying processes in social media
Motivation
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Data Posts and comments about the protest mobilization from public We were on
Bolotnaya Square and well come again from September 2012 to March 2013
Data from Putin must leave Facebook group (participants, friendship links,
locate, language and gender). 18 datasets from 2 December 2012 to 8 May 2013.
Methodology
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Method
Posts and comments from Facebook
public
Interaction social network
Discussion dynamics
Friendship interactions of the protest
group Putin must leave
Methodology
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Actors (Nodes),
Interactions
Date
Time
Attitude to thegroup policy, topic
of the comment,
sentiment, etc.
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Social network (weighted, oriented) represents the
interactions between Facebook users.
Nodes = 540;
Edges = 673 (797) (weighted);
Self-loops = 334 (49.6%);
Without self-loops
N = 306;
E = 340;
The most central nodes are All (2) and
We were on Bolotnaya (1)
Communication network based on We were on BolotnayaColor indicates the attitude to the group:
Green positive;
Blue neutral;
Red negative;
PurpleAll (cant estimate)
Size indicates the indegree centrality
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84 % nodes have degree 1 or 2
90% nodes have indegree 0 or 1
67% nodes have outdegree 1
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After eliminating nodes All and We
were on Bolotnaya
After eliminating node All
Communication network based on We were on Bolotnaya
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After removal two hubs the communication network splits
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0
5
10
15
20
25
0 20 40 60 80 100 120
Numberofco
mments
Hours
Discussion dynamics
Communications in We were on Bolotnaya
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Discussion is active for 15-20 hours
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Topics in public We were on Bolotnaya
0%
5%
10%
15%
20%
25%
30%
35%
Discussion topics
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%
Topic
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Topics in public We were on Bolotnaya
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Discussion topics change rapidly
Number of comment
T
O
P
I
C
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Friendship interactions in group Putin must leave
USA, GB, Italy, etc.
Socialists
Liberals
Louvain method: Finding communities in large networks
Nodes = 2749Edges = 34276
Density = 0,009
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Structure
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Interaction dynamics in Facebook group Putin must leave
2 December 2012
34704 edges
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Interaction dynamics in Facebook group Putin must leave
29 January 2013
36104 edges
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Interaction dynamics in Facebook group Putin must leave
12 February 2013
37292 edges
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Interaction dynamics in Facebook group Putin must leave
25 March 2013
38774 edges
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Interaction dynamics in Facebook group Putin must leave
12 April 2013
38780 edges
d b k l
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Interaction dynamics in Facebook group Putin must leave
4 May 2013
38525 edges
d b k l
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Interaction dynamics in Facebook group Putin must leave
-100%
-80%
-60%
-40%
-20%
0%
20%
40%
60%
80%
100%
12/1/2012 12/21/2012 1/10/2013 1/30/2013 2/19/2013 3/11/2013 3/31/2013 4/20/2013 5/10/2013
Change,%
Date
Indexes dynamics
Nodes
Edges
Modularity
Freedom
March
March against
adoption ban
March for the
rights of theMuscovites
Bolotnaya's
anniversary
P i i i P i l
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Basing on content-analysis and observations weve
distinguished three different types of participants
0%
5%
10%
15%
20%
25%
30%
35%
0 20 40 60 80 100 120 140 160 180 200
Fraction
ofnodes,%
Degree centrality
Degree distribution
Readers justobtain content
without
contributing.Two kinds: Users with low
degree;
Well-known political
persons with very
high degree
Talkers
communicate
and occasionally
post news.
Influencers (key
actors)
actively post and
comment.
Talkers
20%
Influencers
8%
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Participants types in group Putin must leave
Readers
2%Readers
70%
C l i
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Conclusion
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Communication network splits after removal two hubs
Discussion topics change rapidly
Formal network indexes change insignificantly
Actors with high degree dont contribute content
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Thank you for your attention!
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Additi l t i l
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Additional materials
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Additional materials
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Additi l t i l
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0
0.5
1
1.5
2
2.5
3
0 0.5 1 1.5 2 2.5 3
LGNumbero
fnodes
LG Degree centrality
Degree distribution Putin must leave
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Additi l t i l
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0
0.5
1
1.5
2
2.5
3
0 0.5 1 1.5 2 2.5
LGNumberofnode
s
LG Degree
Communication network Degree
distribution
Additional materials
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Additi l t i l
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0.37
0.38
0.39
0.4
0.41
0.42
0.43
11/27/2012 1/6/2013 2/15/2013 3/27/2013 5/6/2013
Modularity
Date
Modularity (t)
Additional materials
CUG-test(Anderson, B.S., Carter T. Butts, and Kathleen M. Carley. 1999. "The Interaction of Size and Density with Graph-Level Indices." Social Networks, 21(3), 239-267.)
Modularity
For ER-networks with the same size and density is 0,19
For Small World networks with the same size and density is 0,48
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Additional materials
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Additional materials
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0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
0 5 10 15 20 25 30 35 40
Fractionof
nodes,%
Degree distribution
Communication network Degree
distributions
Degree
In-degree
Out-degree
Additional matetials
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Additional matetials
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Limitations:
Data only from one Facebook group andone public.
The sample is rather little.
A half of the procedures were manual.
Future work:
Study Vkontakte, Twitter, LiveJournaland Odnoklassniki.
Collect more data (likes, using mobiles,
etc.)
Automated algorithm