TY - GEN
T1 - Wartime Media Monitor (WarMM-2022)
T2 - 7th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, LaTeCH-CLfL 2023
AU - Alyukov, Maxim
AU - Kunilovskaya, Maria
AU - Semenov, Andrei
N1 - Publisher Copyright:
© 2023 Association for Computational Linguistics.
PY - 2023
Y1 - 2023
N2 - This study relies on natural language processing to explore the nature of online communication in Russia during the war on Ukraine in 2022. The analysis of a large corpus of publications in traditional media and on social media identifies massive state interventions aimed at manipulating public opinion. The study relies on expertise in media studies and political science to trace the major themes and strategies of propagandist narratives on three major Russian social media platforms over several months as well as their perception by the users. Distributions of several keyworded pro-war and anti-war topics are examined to reveal the cross-platform specificity of social media audiences. We release WarMM-2022, a 1.7M posts corpus. This corpus includes publications related to the Russia-Ukraine war, which appeared in Russian mass media (February to September 2022) and on social networks (July to September 2022). The corpus can be useful for the development of NLP approaches to propaganda detection and subsequent studies of propaganda campaigns in social sciences in addition to traditional methods, such as content analysis, focus groups, surveys, and experiments.
AB - This study relies on natural language processing to explore the nature of online communication in Russia during the war on Ukraine in 2022. The analysis of a large corpus of publications in traditional media and on social media identifies massive state interventions aimed at manipulating public opinion. The study relies on expertise in media studies and political science to trace the major themes and strategies of propagandist narratives on three major Russian social media platforms over several months as well as their perception by the users. Distributions of several keyworded pro-war and anti-war topics are examined to reveal the cross-platform specificity of social media audiences. We release WarMM-2022, a 1.7M posts corpus. This corpus includes publications related to the Russia-Ukraine war, which appeared in Russian mass media (February to September 2022) and on social networks (July to September 2022). The corpus can be useful for the development of NLP approaches to propaganda detection and subsequent studies of propaganda campaigns in social sciences in addition to traditional methods, such as content analysis, focus groups, surveys, and experiments.
UR - http://www.scopus.com/inward/record.url?scp=85175486272&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85175486272&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85175486272
T3 - EACL 2023 - 7th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, Proceedings of LaTeCH-CLfL 2023
SP - 152
EP - 161
BT - EACL 2023 - 7th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, Proceedings of LaTeCH-CLfL 2023
PB - Association for Computational Linguistics
Y2 - 5 May 2023
ER -