A Progressive Framework for Role-Aware Rumor Resolution

Lei Chen, Guanying Li, Zhongyu Wei, Yang Yang, Baohua Zhou, Qi Zhang, Xuanjing Huang


Abstract
Existing works on rumor resolution have shown great potential in recognizing word appearance and user participation. However, they ignore the intrinsic propagation mechanisms of rumors and present poor adaptive ability when unprecedented news emerges. To exploit the fine-grained rumor diffusion patterns and generalize rumor resolution methods, we formulate a predecessor task to identify triggering posts, and then exploit their characteristics to facilitate rumor verification. We design a tree-structured annotation interface and extend PHEME dataset with labels on the message level. Data analysis shows that triggers play a critical role in verifying rumors and present similar lingual patterns across irrelevant events. We propose a graph-based model considering the direction and interaction of information flow to implement role-aware rumor resolution. Experimental results demonstrate the effectiveness of our proposed model and progressive scheme.
Anthology ID:
2022.coling-1.242
Volume:
Proceedings of the 29th International Conference on Computational Linguistics
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
2748–2758
Language:
URL:
https://aclanthology.org/2022.coling-1.242
DOI:
Bibkey:
Cite (ACL):
Lei Chen, Guanying Li, Zhongyu Wei, Yang Yang, Baohua Zhou, Qi Zhang, and Xuanjing Huang. 2022. A Progressive Framework for Role-Aware Rumor Resolution. In Proceedings of the 29th International Conference on Computational Linguistics, pages 2748–2758, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
Cite (Informal):
A Progressive Framework for Role-Aware Rumor Resolution (Chen et al., COLING 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.coling-1.242.pdf
Code
 lchen96/trigger_identification