Social media warfare: investigating human-bot engagement in English, Japanese and German during the Russo-Ukrainian war on Twitter and Reddit

The Russo-Ukrainian War represents a significant contemporary conflict between two global powers, yet the dynamics of human-bot engagement during this conflict, particularly on social media platforms like Twitter and Reddit, remain underexplored. Existing literature has not adequately addressed how bots and humans interact differently across languages within this geopolitical discourse, nor how these interactions influence the broader narrative. This gap is crucial because understanding these dynamics can reveal how social media is weaponized in modern warfare, influencing public opinion and the course of the conflict. To address this gap, we conducted a comparative analysis of human-bot engagement by examining a longitudinal dataset of tweets and comments related to the Bucha unlawful killings, focusing on three languages: English, Japanese, and German. Our study utilized interlanguage toxicity profiling and network analysis to uncover the temporal trajectories of pro-Russian and pro-Ukrainian actors across these platforms. The analysis of over 20 million tweets and 1 million Reddit comments revealed that bots predominantly operated on Twitter (X), while human users were more active on Reddit. Moreover, we found that English content demonstrated Granger causality with cascade size and depth in minor languages like Japanese and German (p < 0.05), with temporal correlations between human and bot posting frequencies significantly heightening toxicity in English compared to the other languages. These findings not only illuminate the specific behaviors of humans and bots in the early stages of the Russo-Ukrainian War but also provide broader insights into the role of language and platform in social media warfare. By elucidating these network dynamics, our study contributes to a deeper understanding of how digital platforms can be manipulated in geopolitical conflicts, offering critical perspectives for future research and policy-making.

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Publication Details

Journal
EPJ Data Science
Published
2025-02-04
DOI
https://doi.org/10.1140/epjds/s13688-025-00528-y
Citations
1
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
4.20

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article

Social media warfare: investigating human-bot engagement in English, Japanese and German during the Russo-Ukrainian war on Twitter and Reddit

Bin Wang, Kazutoshi Sasahara, Wentao Xu, Jianxun Chu et al.
1 citations
EPJ Data Science
Misinformation and Its Impacts
4.20
article

Social media warfare: investigating human-bot engagement in English, Japanese and German during the Russo-Ukrainian war on Twitter and Reddit

Bin Wang, Kazutoshi Sasahara, Wentao Xu, Jianxun Chu, Zhiwen Hu, Wenlu Fan
article en
1 citations

Abstract

The Russo-Ukrainian War represents a significant contemporary conflict between two global powers, yet the dynamics of human-bot engagement during this conflict, particularly on social media platforms like Twitter and Reddit, remain underexplored. Existing literature has not adequately addressed how bots and humans interact differently across languages within this geopolitical discourse, nor how these interactions influence the broader narrative. This gap is crucial because understanding these dynamics can reveal how social media is weaponized in modern warfare, influencing public opinion and the course of the conflict. To address this gap, we conducted a comparative analysis of human-bot engagement by examining a longitudinal dataset of tweets and comments related to the Bucha unlawful killings, focusing on three languages: English, Japanese, and German. Our study utilized interlanguage toxicity profiling and network analysis to uncover the temporal trajectories of pro-Russian and pro-Ukrainian actors across these platforms. The analysis of over 20 million tweets and 1 million Reddit comments revealed that bots predominantly operated on Twitter (X), while human users were more active on Reddit. Moreover, we found that English content demonstrated Granger causality with cascade size and depth in minor languages like Japanese and German (p < 0.05), with temporal correlations between human and bot posting frequencies significantly heightening toxicity in English compared to the other languages. These findings not only illuminate the specific behaviors of humans and bots in the early stages of the Russo-Ukrainian War but also provide broader insights into the role of language and platform in social media warfare. By elucidating these network dynamics, our study contributes to a deeper understanding of how digital platforms can be manipulated in geopolitical conflicts, offering critical perspectives for future research and policy-making.

EPJ Data ScienceVol. 14(1)
University of Science and Technology of China (CN), Zhejiang Sci-Tech University (CN), Tokyo College of Environment (JP), Japan Science Society (JP), Zhejiang Gongshang University (CN)
University of Science and Technology of China
Openalex Percentile: Top 10%
Misinformation and Its Impacts
4.20
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