Abstract
Fake news’s quick propagation on social media brings severe social ramifications and economic damage. Previous fake news detection usually learn semantic and structural patterns within a single target propagation tree. However, they are usually limited in narrow signals since they do not consider latent information cross other propagation trees. Motivated by a common phenomenon that most fake news is published around a specific hot event/topic, this paper develops a new concept of propagation forest to naturally combine propagation trees in a semantic-aware clustering. We propose a novel Unified Propagation Forest-based framework (UniPF) to fully explore latent correlations between propagation trees to improve fake news detection. Besides, we design a root-induced training strategy, which encourages representations of propagation trees to be closer to their prototypical root nodes. Extensive experiments on four benchmarks consistently suggest the effectiveness and scalability of UniPF.- Anthology ID:
- 2022.coling-1.244
- Volume:
- Proceedings of the 29th International Conference on Computational Linguistics
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 2769–2779
- Language:
- URL:
- https://aclanthology.org/2022.coling-1.244
- DOI:
- Cite (ACL):
- Lingwei Wei, Dou Hu, Yantong Lai, Wei Zhou, and Songlin Hu. 2022. A Unified Propagation Forest-based Framework for Fake News Detection. In Proceedings of the 29th International Conference on Computational Linguistics, pages 2769–2779, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
- Cite (Informal):
- A Unified Propagation Forest-based Framework for Fake News Detection (Wei et al., COLING 2022)
- PDF:
- https://preview.aclanthology.org/insights-reingestion/2022.coling-1.244.pdf