Beyond left and right: Real-world political polarization in twitter discussions on inter-ethnic conflicts

Research output

2 Citations (Scopus)

Abstract

Studies of political polarization in social media demonstrate mixed evidence for whether discussions necessarily evolve into left and right ideological echo chambers. Recent research shows that, for political and issue-based discussions, patterns of user clusterization may differ significantly, but that cross-cultural evidence of the polarization of users on certain issues is close to non-existent. Furthermore, most of the studies developed network proxies to detect users’ grouping, rarely taking into account the content of the Tweets themselves. Our contribution to this scholarly discussion is founded upon the detection of polarization based on attitudes towards political actors expressed by users in Germany, the USA and Russia within discussions on inter-ethnic conflicts. For this exploratory study, we develop a mixed-method approach to detecting user grouping that includes: Crawling for data collection; expert coding of Tweets; user clusterization based on user attitudes; construction of word frequency vocabularies; and graph visualization. Our results show that, in all the three cases, the groups detected are far from being conventionally left or right, but rather that their views combine anti-institutionalism, nationalism, and pro- and anti-minority views in varying degrees. In addition to this, more than two threads of political debate may co-exist in the same discussion. Thus, we show that the debate that sees Twitter as either a platform of ‘echo chambering’ or ‘opinion crossroads’ may be misleading. In our opinion, the role of local political context in shaping (and explaining) user clusterization should not be under-estimated.

Original languageEnglish
Pages (from-to)119-132
JournalMedia and Communication
Volume7
Issue number3
DOIs
Publication statusPublished - Aug 2019

Fingerprint

ethnic conflict
twitter
polarization
Polarization
Visualization
grouping
minority
institutionalism
political actor
social media
chamber
visualization
evidence
nationalism
coding
vocabulary
Russia
expert

Scopus subject areas

  • Communication

Cite this

@article{fc8ea5f8e9b140c0a8e195de3ffbe4e5,
title = "Beyond left and right: Real-world political polarization in twitter discussions on inter-ethnic conflicts",
abstract = "Studies of political polarization in social media demonstrate mixed evidence for whether discussions necessarily evolve into left and right ideological echo chambers. Recent research shows that, for political and issue-based discussions, patterns of user clusterization may differ significantly, but that cross-cultural evidence of the polarization of users on certain issues is close to non-existent. Furthermore, most of the studies developed network proxies to detect users’ grouping, rarely taking into account the content of the Tweets themselves. Our contribution to this scholarly discussion is founded upon the detection of polarization based on attitudes towards political actors expressed by users in Germany, the USA and Russia within discussions on inter-ethnic conflicts. For this exploratory study, we develop a mixed-method approach to detecting user grouping that includes: Crawling for data collection; expert coding of Tweets; user clusterization based on user attitudes; construction of word frequency vocabularies; and graph visualization. Our results show that, in all the three cases, the groups detected are far from being conventionally left or right, but rather that their views combine anti-institutionalism, nationalism, and pro- and anti-minority views in varying degrees. In addition to this, more than two threads of political debate may co-exist in the same discussion. Thus, we show that the debate that sees Twitter as either a platform of ‘echo chambering’ or ‘opinion crossroads’ may be misleading. In our opinion, the role of local political context in shaping (and explaining) user clusterization should not be under-estimated.",
keywords = "Echo chamber, Inter-ethnic conflict, Political polarization, Social media, Twitter, CLIMATE-CHANGE, MODEL, inter-ethnic conflict, political polarization, DISSENT, echo chamber, social media, COMMUNICATION",
author = "Bodrunova, {Svetlana S.} and Ivan Blekanov and Anna Smoliarova and Anna Litvinenko",
year = "2019",
month = "8",
doi = "10.17645/mac.v7i3.1934",
language = "English",
volume = "7",
pages = "119--132",
journal = "Media and Communication",
issn = "2183-2439",
publisher = "Cogitatio Press",
number = "3",

}

TY - JOUR

T1 - Beyond left and right

T2 - Real-world political polarization in twitter discussions on inter-ethnic conflicts

AU - Bodrunova, Svetlana S.

AU - Blekanov, Ivan

AU - Smoliarova, Anna

AU - Litvinenko, Anna

PY - 2019/8

Y1 - 2019/8

N2 - Studies of political polarization in social media demonstrate mixed evidence for whether discussions necessarily evolve into left and right ideological echo chambers. Recent research shows that, for political and issue-based discussions, patterns of user clusterization may differ significantly, but that cross-cultural evidence of the polarization of users on certain issues is close to non-existent. Furthermore, most of the studies developed network proxies to detect users’ grouping, rarely taking into account the content of the Tweets themselves. Our contribution to this scholarly discussion is founded upon the detection of polarization based on attitudes towards political actors expressed by users in Germany, the USA and Russia within discussions on inter-ethnic conflicts. For this exploratory study, we develop a mixed-method approach to detecting user grouping that includes: Crawling for data collection; expert coding of Tweets; user clusterization based on user attitudes; construction of word frequency vocabularies; and graph visualization. Our results show that, in all the three cases, the groups detected are far from being conventionally left or right, but rather that their views combine anti-institutionalism, nationalism, and pro- and anti-minority views in varying degrees. In addition to this, more than two threads of political debate may co-exist in the same discussion. Thus, we show that the debate that sees Twitter as either a platform of ‘echo chambering’ or ‘opinion crossroads’ may be misleading. In our opinion, the role of local political context in shaping (and explaining) user clusterization should not be under-estimated.

AB - Studies of political polarization in social media demonstrate mixed evidence for whether discussions necessarily evolve into left and right ideological echo chambers. Recent research shows that, for political and issue-based discussions, patterns of user clusterization may differ significantly, but that cross-cultural evidence of the polarization of users on certain issues is close to non-existent. Furthermore, most of the studies developed network proxies to detect users’ grouping, rarely taking into account the content of the Tweets themselves. Our contribution to this scholarly discussion is founded upon the detection of polarization based on attitudes towards political actors expressed by users in Germany, the USA and Russia within discussions on inter-ethnic conflicts. For this exploratory study, we develop a mixed-method approach to detecting user grouping that includes: Crawling for data collection; expert coding of Tweets; user clusterization based on user attitudes; construction of word frequency vocabularies; and graph visualization. Our results show that, in all the three cases, the groups detected are far from being conventionally left or right, but rather that their views combine anti-institutionalism, nationalism, and pro- and anti-minority views in varying degrees. In addition to this, more than two threads of political debate may co-exist in the same discussion. Thus, we show that the debate that sees Twitter as either a platform of ‘echo chambering’ or ‘opinion crossroads’ may be misleading. In our opinion, the role of local political context in shaping (and explaining) user clusterization should not be under-estimated.

KW - Echo chamber

KW - Inter-ethnic conflict

KW - Political polarization

KW - Social media

KW - Twitter

KW - CLIMATE-CHANGE

KW - MODEL

KW - inter-ethnic conflict

KW - political polarization

KW - DISSENT

KW - echo chamber

KW - social media

KW - COMMUNICATION

UR - http://www.scopus.com/inward/record.url?scp=85073275547&partnerID=8YFLogxK

U2 - 10.17645/mac.v7i3.1934

DO - 10.17645/mac.v7i3.1934

M3 - Article

AN - SCOPUS:85073275547

VL - 7

SP - 119

EP - 132

JO - Media and Communication

JF - Media and Communication

SN - 2183-2439

IS - 3

ER -