Modeling Discourse Profiles in Climate Misinformation Discourse
Prior work on climate misinformation detection typically classifies individual comments or claims using text alone. This framing overlooks a key property of online climate discourse: misinformation is often produced, reinforced, and sustained through recurring rhetorical patterns that reappear across comments and threads. Using a large-scale TikTok climate discourse dataset, we construct discourse profiles by clustering climate-related comments into recurring rhetorical patterns. We then incorporate these profiles into fine-grained climate misinformation classifiers using a late-fusion architecture. Under video-disjoint evaluation across three training seeds, discourse-profile-aware model...
| Authors | Ge Gao, Zhengyang Shan, Bryan A. Plummer et al. |
|---|---|
| Primary category | cs.CL |
| Published | 17 October 2026 |
| Last updated at source | 17 October 2026 |
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