Abstract
This paper describes our system submitted to SemEval 2019 Task 7: RumourEval 2019: Determining Rumour Veracity and Support for Rumours, Subtask A (Gorrell et al., 2019). The challenge focused on classifying whether posts from Twitter and Reddit support, deny, query, or comment a hidden rumour, truthfulness of which is the topic of an underlying discussion thread. We formulate the problem as a stance classification, determining the rumour stance of a post with respect to the previous thread post and the source thread post. The recent BERT architecture was employed to build an end-to-end system which has reached the F1 score of 61.67 % on the provided test data. Without any hand-crafted feature, the system finished at the 2nd place in the competition, only 0.2 % behind the winner.- Anthology ID:
- S19-2192
- Volume:
- Proceedings of the 13th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2019
- Address:
- Minneapolis, Minnesota, USA
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1097–1104
- Language:
- URL:
- https://aclanthology.org/S19-2192
- DOI:
- 10.18653/v1/S19-2192
- Cite (ACL):
- Martin Fajcik, Pavel Smrz, and Lukas Burget. 2019. BUT-FIT at SemEval-2019 Task 7: Determining the Rumour Stance with Pre-Trained Deep Bidirectional Transformers. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 1097–1104, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
- Cite (Informal):
- BUT-FIT at SemEval-2019 Task 7: Determining the Rumour Stance with Pre-Trained Deep Bidirectional Transformers (Fajcik et al., SemEval 2019)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/S19-2192.pdf
- Code
- MFajcik/RumourEval2019