Abstract
Despite recent progress in automated rumour verification, little has been done on evaluating rumours in a real-world setting. We advance the state-of-the-art on the PHEME dataset, which consists of Twitter response threads collected as a rumour was unfolding. We automatically collect evidence relevant to PHEME and use it to construct knowledge graphs in a time-sensitive manner, excluding information post-dating rumour emergence. We identify discrepancies between the evidence retrieved and PHEME’s labels, which are discussed in detail and amended to release an updated dataset. We develop a novel knowledge graph approach which finds paths linking disjoint fragments of evidence. Our rumour verification model which combines evidence from the graph outperforms the state-of-the-art on PHEME and has superior generisability when evaluated on a temporally distant rumour verification dataset.- Anthology ID:
- 2024.lrec-main.860
- Volume:
- Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
- Venues:
- LREC | COLING
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 9843–9853
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.860
- DOI:
- Cite (ACL):
- John Dougrez-Lewis, Elena Kochkina, Maria Liakata, and Yulan He. 2024. Knowledge Graphs for Real-World Rumour Verification. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 9843–9853, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- Knowledge Graphs for Real-World Rumour Verification (Dougrez-Lewis et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-5/2024.lrec-main.860.pdf