# Belief Is All You Need: Signed Belief Graph Neural Networks for Topic Modeling in Conspiratorial Discourse

> Source: <https://aclanthology.org/2026.nlpcss-1.20/>
> Published: 2026-07-13 00:00:00+00:00

[Belief Is All You Need: Signed Belief Graph Neural Networks for Topic Modeling in Conspiratorial Discourse](https://aclanthology.org/2026.nlpcss-1.20.pdf)

[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](https://aclanthology.org/2026.nlpcss-1.20/). In*Proceedings 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)