Saint Petersburg
State University
Role of Twitter in formation of political agenda
in various socio-political contexts:
the cases of discussions on migrants
in Russia and Germany
Svetlana Bodrunova, PhD,
Anna Litvinenko, PhD
School of Journalism and Mass Communications
St. Petersburg State University
Saint Petersburg
State University
Theoretical premises
1. Hybridization of media systems (Chadwick 2011, 2013):
- Tech-based growth of the web segment of media systems brings in
new societal and political cleavages
- Difference in hybridization patterns depends most upon national
socio-political conditions (Adam&Pfetsch 2011)
2. Media-constructed public sphere:
- Media as ‘junctions’ of the public sphere => mediatization?
3. Network(ed) communication theory:
-
Formation of closed-up communicative milieus (‘echo chambers’)
-
The idea of ‘spill-overs’ (online to offline, traditional/new media)
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Twitter as a communicative milieu:
optimism vs. pessimism
• Twitter as the milieu of platform-limited horizontal
communication with a big news alerts potential
(Mancini&Mazzoni 2013, Vaccari et al. 2013)
• Twitter as a de-politicized space for gaming, dating,
and chats (Fuchs 2014: Chapter 8)
• Can Twitter be a ‘crossroads of opinion’ in the
online public sphere?
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Public Sphere in Russia and in Germany



Russia in 21st century is a fundamentally fragmented society
(Zubarevich 2011, 2013): «Four Russias»
Bodrunova, Litvinenko 2013: formation of the public countersphere in Russia of 2008-2012
Germany, in these terms, has developed a more solid society,
with the differences between Eastern and Western part
gradually diminishing in many terms; the only striking similarity
is huge urban migrant population from the southern direction
still under-represented in the media content. Germany has a
large number of citizens with migrant background and big
diasporas, e.g. Turkish- and Russian-speaking communities
which, in terms of media use, often differ from national
average indicators (Sauer 2010)
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State University
Project «Political agendas
in hybrid media systems»
•
Research team: Svetlana Bodrunova, Dmitry Gavra, Anna Litvinenko,
Alena Savizkaya, Anna Smolyarova, Alexandr Yakunin
•
Research upon structural and framing features of Twitter
discussions in Russia and Germany
• Roles of media accounts in discussions upon polarizing issues
-
overall mediatization
linkages between media and non-media accounts (the ‘crossroads’
issue)
•
A case of social polarization: anti-migrant bashings in Biryulyovo
district of Moscow in October 2013
•
A ‘calm’ period in Russia and in Germany (March 2014)
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State University
Mixed methodology
1.
2.
3.
4.
Web crawling based on pre-selected hashtags
Frame analysis based on coding of tweets
Descriptive statistics
Discourse analysis (including semantic groups
of lexicon and their interpretation)
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Time-series graphs
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STRUCTURE OF THE DISCUSSION:
results of web crawling
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Web graph:
Russia,
Biryulyovo
- political actors
- media
- ordinary users
- fake/spam
Webgraph:
Germany
- Political actors
- Media
- Ordinary users
- NGOs
Webgraph:
Russia
- Political actors
- Media
- Ordinary users
- Nationalist users
- Official accounts
- NGOs
- Spin-doctoring(!)
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FEATURES OF THE DISCOURSE
15% of tweeets put blame on someone
Just ONE tweet of 673 tells
‘it is the whole society to be blamed’
10% contain nationalist speech
11% contain hate speech
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Features of the discourse:
discussion topics
Discussion topics
350
300
287
250
228
200
Number of tweets
150
118
100
50
27
16
0
Non-violent
topics
Bashings and
police actions
Killings
Other
Nondefinable
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Features of the discourse:
Tweeters’ mood
Tweeters' mood
600
516
500
400
300
200
114
100
19
14
12
Affective positive
Constructive
motivational
0
Destructive
motivational
Affective negative Neutral/Ambivalent
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Features of the discourse:
Tweeters’ mood
Emotional vs. rational discourse
350
291
300
250
200
197
Ntweets
150
113
100
37
50
17
0
Details / witness
Facts
Emotional
Rational
Call for action
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State University
Polarization of the public sphere on Twitter
Public sphere in Twitter:
from anti- to pro-establishment users
7
6
5
4
3
2
1
1
16
31
46
61
76
91
106
121
136
151
166
181
196
211
226
241
256
271
286
301
316
331
346
361
376
391
406
421
436
451
466
481
496
511
526
541
556
571
586
601
616
631
646
661
676
0
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Features of the discourse:
origins of discussants
Origins of discussants: Migrants vs. Russians
450
-2 Non-institutional migrants
413
400
350
-1 Migrant/diaspora actors or
media
300
250
244
200
150
0 Citizens or actors from third
contries
1 Russian actors or media
100
2 Russian citizens
50
0
9
0
-2
-1
0
0
1
2
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State University
Features of the discourse:
who is to be blamed?
Who is to be blamed?
25
23
23
20
20
20
15
10
6
6
Ntweets
5
1
2
1
0
15% =
100 tweets
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Semantic analysis:
First 600 stems from the word dataset
#бирюлево
16
66 5
8
14
86
21
28
42
28
42
34
35
37
41
Events
Politics&politicians
Judgment lexics
Migrants
Media
City
Police and their activity
Protests and pogromes
Killing Egor Scherbakov
People and their features
Russian and the nation
The warehouse
External territories
Economics
Other isuues
Positive lexics
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MEDIATIZATION OF THE DISCUSSION
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State University
Mediatization of the discussion:
media dominate in N of tweets
Communicative status
of the discussants’ tweets
350
290
300
250
194
200
163
0 non-witness, 1 witness,
2 media, 3 experts
150
100
50
30
0
0
1
2
3
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State University
Some results in hashtagging
- mediatization really high: «breaking news», «news», «novosti», «they
say that…», «RIA», «media», «Lifenews», «RT»
- national-level political actors: Putin, ‘United Russia’ party, Navalny,
Public Chamber
- scarce aspect thinking: introduction of visas, football
- other issues: LGBT; corruption.
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‘Discussion triggers’
• mediatization: both real and fake!
• media of various Russian public spheres
• nationalists outperform migrants
• the role of Public Chamber
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Positions of media in the discussion
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State University
Tweeted media content vs. involved media content
70%
64%
60%
50%
42%
40%
37%
Tweeted
Referenced
31%
30%
20%
19%
10%
0
0%
Hybrid
N = 677 tweets
Online-only
Web 2.0
5%
1%
Twitter only
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State University
Conclusion
Twitter in Russia shows a bigger potential for becoming a real
"crossroads of opinions", in contrast to the Russian Facebook
where anti-governmental discourse predominates, as well as to
Vkontakte where political debate is much less noticeable and is
encapsulated in closed-up communities. BUT underrepresentation of migrant community in Twitter obstacles this.
In Russian Twitter, hybrid pro-elite media dominate represented by
lifenews_ru, izvestia_ru, pravda.ru, RT_russia, onlinekpru etc.,
although the anti-mainstreem media are also among influencers
(GraniTweet, SvobodaRadio, MaloverjanBBC, ru_rbc).
In general, the case study supported hypothesis about the different
role of Twitter in different socio-political contexts.
Thank you
for your attention!