Graph-based framework detects disinformation narratives across Telegram channels
Weak supervision + propagation graphs uncover coordinated amplification in Ukraine-Russia info war.
A graph-based framework is proposed for detecting disinformation narratives in Telegram ecosystems. The approach combines weak supervision with propagation graph analysis, aggregating semantically related claims into narrative-level clusters and modeling their diffusion across interconnected channels. 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.
- Combines weak supervision with propagation graph analysis to detect disinformation narratives
- Aggregates semantically related claims into narrative-level clusters and models cross-channel diffusion
- Integrated textual and network signals enable scalable detection of coordinated amplification
Why It Matters
Offers a scalable tool to uncover coordinated disinformation campaigns in messaging platforms, critical for information warfare monitoring.