In recent years, disinformation has increasingly proliferated across social networks. The firing of fact-checkers from Meta and the disbanding of Twitter's Trust and Safety Council suggest that this trend will continue to escalate. While disinformation sources (e.g., social network accounts) can sometimes be identified, new accounts emerge daily, making tracking a moving target. In this work, we propose a graph-based methodology to discover previously unknown Telegram accounts that spread disinformation. Starting from a set of verified disinformation groups, we examine their interconnections and identify new accounts that contribute to the dissemination of false narratives. Our approach is language-agnostic, as it relies solely on structural relationships between accounts rather than analyzing their message content. Using this approach, we identify 37 previously unknown disinformation channels (a threefold increase). We demonstrate that Telegram channels display extremely dogmatic behavior with up to 80% of messages being labeled as propaganda. Our findings reveal that misinformation on Telegram spreads within tightly interconnected clusters, in some cases, with over 86K identical messages being shared to multiple channels, suggesting coordinated disinformation campaigns.

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