@InProceedings{fajcik-smrz-burget:2019:S19-2,
  author    = {Fajcik, Martin  and  Smrz, Pavel  and  Burget, Lukas},
  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},
  month     = {June},
  year      = {2019},
  address   = {Minneapolis, Minnesota, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {1097--1104},
  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.},
  url       = {http://www.aclweb.org/anthology/S19-2192}
}