mlsanityData to 13 Oct 2026

BUT-FIT at SemEval-2019 Task 7: Determining the Rumour Stance with Pre-Trained Deep Bidirectional Transformers

arXiv 1902.10126 ↗First posted 25 Feb 2019cs.CL cs.AI cs.LGcited by 7

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Abstract (arXiv)

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. It finished at the 2nd place in the competition, without any hand-crafted features, only 0.2% behind the winner.

Key facts. Cited by 7 papers in the map (data through 13 Oct 2026). First posted on arXiv 25 Feb 2019.

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7 papers.