Publication result detail

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

FAJČÍK, M.; BURGET, L.; SMRŽ, P.

Original Title

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

English Title

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

Type

Paper in proceedings (conference paper)

Original 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.

English 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.

Keywords

rumour stance, hidden rumour stance, BERT, transformer, classification, stance classification, twitter post classification, reddit post classification, thread post classification, semeval, rumoureval

Key words in English

rumour stance, hidden rumour stance, BERT, transformer, classification, stance classification, twitter post classification, reddit post classification, thread post classification, semeval, rumoureval

Authors

FAJČÍK, M.; BURGET, L.; SMRŽ, P.

RIV year

2020

Released

26.06.2019

Publisher

Association for Computational Linguistics

Location

Minneapolis, Minnesota

ISBN

978-1-950737-06-2

Book

Proceedings of the 13th International Workshop on Semantic Evaluation

Pages from

1097

Pages to

1104

Pages count

8

URL

https://aclweb.org/anthology/papers/S/S19/S19-2192/

BibTex

@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/"
}