Modeling Information Narrative Detection and Evolution on Telegram during the Russia-Ukraine War
Patrick Gerard, Svitlana Volkova, Louis Penafiel, Kristina Lerman, Tim, Weninger

TL;DR
This paper introduces a novel method to model and analyze the evolution of information narratives on Telegram during the Russia-Ukraine conflict, revealing disparities and mechanisms behind narrative changes in pro-Russian and pro-Ukrainian communities.
Contribution
It presents a new approach for modeling narrative evolution and uncovering underlying mechanisms, addressing gaps in existing research on dynamic information environments during conflicts.
Findings
Substantial disparities in narratives between communities
Identification of key themes driving narrative evolution
Analysis of influences shaping narrative development
Abstract
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…
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Taxonomy
TopicsOpportunistic and Delay-Tolerant Networks · Opinion Dynamics and Social Influence
