Modeling Information Narrative Detection and Evolution on Telegram during the Russia-Ukraine War
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866909313017053184 |
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| author | Gerard, Patrick Volkova, Svitlana Penafiel, Louis Lerman, Kristina Weninger, Tim |
| author_facet | Gerard, Patrick Volkova, Svitlana Penafiel, Louis Lerman, Kristina Weninger, Tim |
| contents | Following the Russian Federation's full-scale invasion of Ukraine in February 2022, a multitude of information narratives emerged within both pro-Russian and pro-Ukrainian communities online. As the conflict progresses, so too do the information narratives, constantly adapting and influencing local and global community perceptions and attitudes. This dynamic nature of the evolving information environment (IE) underscores a critical need to fully discern how narratives evolve and affect online communities. Existing research, however, often fails to capture information narrative evolution, overlooking both the fluid nature of narratives and the internal mechanisms that drive their evolution. Recognizing this, we introduce a novel approach designed to both model narrative evolution and uncover the underlying mechanisms driving them. In this work we perform a comparative discourse analysis across communities on Telegram covering the initial three months following the invasion. First, we uncover substantial disparities in narratives and perceptions between pro-Russian and pro-Ukrainian communities. Then, we probe deeper into prevalent narratives of each group, identifying key themes and examining the underlying mechanisms fueling their evolution. Finally, we explore influences and factors that may shape the development and spread of narratives. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_07684 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Modeling Information Narrative Detection and Evolution on Telegram during the Russia-Ukraine War Gerard, Patrick Volkova, Svitlana Penafiel, Louis Lerman, Kristina Weninger, Tim Social and Information Networks Artificial Intelligence Following the Russian Federation's full-scale invasion of Ukraine in February 2022, a multitude of information narratives emerged within both pro-Russian and pro-Ukrainian communities online. As the conflict progresses, so too do the information narratives, constantly adapting and influencing local and global community perceptions and attitudes. This dynamic nature of the evolving information environment (IE) underscores a critical need to fully discern how narratives evolve and affect online communities. Existing research, however, often fails to capture information narrative evolution, overlooking both the fluid nature of narratives and the internal mechanisms that drive their evolution. Recognizing this, we introduce a novel approach designed to both model narrative evolution and uncover the underlying mechanisms driving them. In this work we perform a comparative discourse analysis across communities on Telegram covering the initial three months following the invasion. First, we uncover substantial disparities in narratives and perceptions between pro-Russian and pro-Ukrainian communities. Then, we probe deeper into prevalent narratives of each group, identifying key themes and examining the underlying mechanisms fueling their evolution. Finally, we explore influences and factors that may shape the development and spread of narratives. |
| title | Modeling Information Narrative Detection and Evolution on Telegram during the Russia-Ukraine War |
| topic | Social and Information Networks Artificial Intelligence |
| url | https://arxiv.org/abs/2409.07684 |