Detail výsledku
BUT-FIT at SemEval-2019 Task 7: Determining the Rumour Stance with Pre-Trained Deep Bidirectional Transformers
Burget Lukáš, doc. Ing., Ph.D., UPGM (FIT)
Smrž Pavel, doc. RNDr., Ph.D., UPGM (FIT)
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.
rumour stance, hidden rumour stance, BERT, transformer, classification, stance classification, twitter post classification, reddit post classification, thread post classification, semeval, rumoureval
@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/"
}