@inproceedings{alyukov-etal-2023-wartime,
title = "Wartime Media Monitor ({W}ar{MM}-2022): A Study of Information Manipulation on {R}ussian Social Media during the {R}ussia-{U}kraine War",
author = "Alyukov, Maxim and
Kunilovskaya, Maria and
Semenov, Andrei",
editor = "Degaetano-Ortlieb, Stefania and
Kazantseva, Anna and
Reiter, Nils and
Szpakowicz, Stan",
booktitle = "Proceedings of the 7th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.latechclfl-1.17",
doi = "10.18653/v1/2023.latechclfl-1.17",
pages = "152--161",
abstract = "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 the 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 and on social networks between February and 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.",
}
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<abstract>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 the 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 and on social networks between February and 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.</abstract>
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%0 Conference Proceedings
%T Wartime Media Monitor (WarMM-2022): A Study of Information Manipulation on Russian Social Media during the Russia-Ukraine War
%A Alyukov, Maxim
%A Kunilovskaya, Maria
%A Semenov, Andrei
%Y Degaetano-Ortlieb, Stefania
%Y Kazantseva, Anna
%Y Reiter, Nils
%Y Szpakowicz, Stan
%S Proceedings of the 7th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
%D 2023
%8 May
%I Association for Computational Linguistics
%C Dubrovnik, Croatia
%F alyukov-etal-2023-wartime
%X 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 the 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 and on social networks between February and 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.
%R 10.18653/v1/2023.latechclfl-1.17
%U https://aclanthology.org/2023.latechclfl-1.17
%U https://doi.org/10.18653/v1/2023.latechclfl-1.17
%P 152-161
Markdown (Informal)
[Wartime Media Monitor (WarMM-2022): A Study of Information Manipulation on Russian Social Media during the Russia-Ukraine War](https://aclanthology.org/2023.latechclfl-1.17) (Alyukov et al., LaTeCHCLfL 2023)
ACL