Graph-Based Detection of Disinformation Narrative Diffusion between Russian and Ukrainian Telegram Channels

• URL: http://arxiv.org/abs/2607.11894v1
• Date: Sat, 09 May 2026 08:35:16 GMT
• Title: Graph-Based Detection of Disinformation Narrative Diffusion between Russian and Ukrainian Telegram Channels
• Abstract summary: We propose a graph-based framework for identifying and analyzing disinformation narratives in Telegram ecosystems.<n>The approach aggregates semantically related claims into narrative-level clusters and models their diffusion across interconnected channels.
• Score: 3.307377521803888
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Detecting disinformation narratives on social media is challenging due to the scale of amplification, rapid evolution, and linguistic variability of online content. We propose a graph-based framework for identifying and analyzing disinformation narratives in Telegram ecosystems by combining weak supervision with propagation graph analysis. The approach aggregates semantically related claims into narrative-level clusters and models their diffusion across interconnected channels. This enables the detection of coordinated narrative amplification that is difficult to capture through post-level analysis alone. Our results demonstrate that integrating textual signals with network structure provides a scalable method for detecting disinformation narratives and offers insights into how they propagate within large-scale messaging environments.

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