Publication Details
BUT-FIT at SemEval-2019 Task 7: Determining the Rumour Stance with Pre-Trained Deep Bidirectional Transformers
Burget Lukáš, doc. Ing., Ph.D. (DCGM)
Smrž Pavel, doc. RNDr., Ph.D. (DCGM)
rumour stance, hidden rumour stance, BERT, transformer, classification, stance
classification, twitter post classification, reddit post classification, thread
post classification, semeval, rumoureval
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.
@inproceedings{BUT158076,
author="Martin {Fajčík} and Lukáš {Burget} and Pavel {Smrž}",
title="BUT-FIT at SemEval-2019 Task 7: Determining the Rumour Stance with Pre-Trained Deep Bidirectional Transformers",
booktitle="Proceedings of the 13th International Workshop on Semantic Evaluation",
year="2019",
pages="1097--1104",
publisher="Association for Computational Linguistics",
address="Minneapolis, Minnesota",
isbn="978-1-950737-06-2",
url="https://aclweb.org/anthology/papers/S/S19/S19-2192/"
}