MITRE at SemEval-2019 Task 5: Transfer Learning for Multilingual Hate Speech Detection

Abigail Gertner, John Henderson, Elizabeth Merkhofer, Amy Marsh, Ben Wellner, Guido Zarrella


Abstract
This paper describes MITRE’s participation in SemEval-2019 Task 5, HatEval: Multilingual detection of hate speech against immigrants and women in Twitter. The techniques explored range from simple bag-of-ngrams classifiers to neural architectures with varied attention mechanisms. We describe several styles of transfer learning from auxiliary tasks, including a novel method for adapting pre-trained BERT models to Twitter data. Logistic regression ties the systems together into an ensemble submitted for evaluation. The resulting system was used to produce predictions for all four HatEval subtasks, achieving the best mean rank of all teams that participated in all four conditions.
Anthology ID:
S19-2080
Volume:
Proceedings of the 13th International Workshop on Semantic Evaluation
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota, USA
Editors:
Jonathan May, Ekaterina Shutova, Aurelie Herbelot, Xiaodan Zhu, Marianna Apidianaki, Saif M. Mohammad
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
453–459
Language:
URL:
https://aclanthology.org/S19-2080
DOI:
10.18653/v1/S19-2080
Bibkey:
Cite (ACL):
Abigail Gertner, John Henderson, Elizabeth Merkhofer, Amy Marsh, Ben Wellner, and Guido Zarrella. 2019. MITRE at SemEval-2019 Task 5: Transfer Learning for Multilingual Hate Speech Detection. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 453–459, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):
MITRE at SemEval-2019 Task 5: Transfer Learning for Multilingual Hate Speech Detection (Gertner et al., SemEval 2019)
Copy Citation:
PDF:
https://aclanthology.org/S19-2080.pdf