Sunbelt-Dokuka-v5.pptx

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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

[email protected]

www.newmediacenter.ru

Sunbelt XXXIII

May 23, 2013

Center for the Studyof New Media and

Society
mailto:[email protected]://www.newmediacenter.ru/http://www.newmediacenter.ru/mailto:[email protected]


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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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29 January 2013

36104 edges


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12 February 2013

37292 edges


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25 March 2013

38774 edges


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12 April 2013

38780 edges

d b k l


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4 May 2013

38525 edges

d b k l


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-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!


Additi l t i l


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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


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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)


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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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

Sunbelt-Dokuka-v5.pptx

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