Study examines misinformation dynamics on Telegram, highlighting challenges in profiling malicious actors and implications for understanding misinformation.
This study examines methodological challenges in collecting and analysing misinformation on Telegram (software) and develops a platform-sensitive conceptual framework for identifying malicious actors. Addressing gaps in existing research, the framework accounts for Telegram’s distinctive features, including limited moderation, privacy affordances, and channel-based dissemination. The study combines a structured literature review with the development and empirical testing of a four-dimensional framework encompassing creators, message content, target victims, and social context. The framework is applied to the anti-vaccination ecosystem on Telegram using a dataset of 7550 messages collected from 151 public channels and manually annotated. The results demonstrate both the analytical value of structured content-based approaches and their limitations in attributing malicious activity without behavioural and network-level data.
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Skaržauskienė et al. (2026) studied this question.
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