[Soorya Ram Shimgekar](/people/soorya-ram-shimgekar/),
[Abhay Goyal](/people/abhay-goyal/unverified/),
[Roy Ka-Wei Lee](/people/roy-ka-wei-lee/),
[Koustuv Saha](/people/koustuv-saha/),
[Pi Zonooz](/people/pi-zonooz/unverified/),
[Edson C Tandoc Jr](/people/edson-c-tandoc-jr/unverified/),
[Navin Kumar](/people/navin-kumar/unverified/)
Abstract
Conspiratorial discourse is increasingly present in online communication, yet how it is organized across discussion topics remains unclear. We analyze Singapore-based Telegram groups to examine how conspiratorial content appears within everyday conversations rather than isolated echo chambers. To better capture the structure of such discussions, we propose a two-stage framework for topic modeling tailored to conspiratorial posts. First, a RoBERTa-large classifier identifies conspiratorial messages (F1 = 0.866) using 2,000 expert-annotated examples. We then construct a graph where connections reflect textual similarity and conspiratorial stance. This graph is modeled using a Signed Belief Graph Neural Network (SiBeGNN), which learns message embeddings that distinguish conspiratorial from non-conspiratorial content. We apply hierarchical clustering on these embeddings to perform topic modeling over 553,648 Telegram messages, producing seven topic clusters: General Legal Topics, Medical Concerns, Media Discussions, Banking and Finance, Contradictions in Authority, Group Moderation, and General Discussions. Our method substantially outperforms standard embedding-based clustering approaches (cDBI = 8.38 vs. 13.60–67.27), with manual evaluation showing 88% inter-rater agreement in cluster interpretation. The results show that conspiratorial content appears across multiple everyday topics, including finance, law, and daily life, rather than forming isolated thematic communities.- Anthology ID:
- 2026.nlpcss-1.20
- Volume:
[Proceedings of the Seventh Workshop on Natural Language Processing and Computational Social Science](/volumes/2026.nlpcss-1/)- Month:
- July
- Year:
- 2026
- Address:
- San Diego
- Editors:
[Dallas Card](/people/dallas-card/),[Anjalie Field](/people/anjalie-field/),[Katherine Keith](/people/katherine-keith/),[Julia Mendelsohn](/people/julia-mendelsohn/)- Venues:
[NLP+CSS](/venues/nlpcss/)|[WS](/venues/ws/)- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 341–355
- Language:
- URL:
[https://aclanthology.org/2026.nlpcss-1.20/](https://aclanthology.org/2026.nlpcss-1.20/)- DOI:
- Cite (ACL):
- Soorya Ram Shimgekar, Abhay Goyal, Roy Ka-Wei Lee, Koustuv Saha, Pi Zonooz, Edson C Tandoc Jr, and Navin Kumar. 2026. Belief Is All You Need: Signed Belief Graph Neural Networks for Topic Modeling in Conspiratorial Discourse. InProceedings of the Seventh Workshop on Natural Language Processing and Computational Social Science, pages 341–355, San Diego. Association for Computational Linguistics. - Cite (Informal):
[Belief Is All You Need: Signed Belief Graph Neural Networks for Topic Modeling in Conspiratorial Discourse](https://aclanthology.org/2026.nlpcss-1.20/)(Shimgekar et al., NLP+CSS 2026)- PDF:
[https://aclanthology.org/2026.nlpcss-1.20.pdf](https://aclanthology.org/2026.nlpcss-1.20.pdf)