YNU-HPCC at SemEval-2019 Task 6: Identifying and Categorising Offensive Language on Twitter

Chengjin Zhou, Jin Wang, Xuejie Zhang


Abstract
This document describes the submission of team YNU-HPCC to SemEval-2019 for three Sub-tasks of Task 6: Sub-task A, Sub-task B, and Sub-task C. We have submitted four systems to identify and categorise offensive language. The first subsystem is an attention-based 2-layer bidirectional long short-term memory (BiLSTM). The second subsystem is a voting ensemble of four different deep learning architectures. The third subsystem is a stacking ensemble of four different deep learning architectures. Finally, the fourth subsystem is a bidirectional encoder representations from transformers (BERT) model. Among our models, in Sub-task A, our first subsystem performed the best, ranking 16th among 103 teams; in Sub-task B, the second subsystem performed the best, ranking 12th among 75 teams; in Sub-task C, the fourth subsystem performed best, ranking 4th among 65 teams.
Anthology ID:
S19-2142
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:
812–817
Language:
URL:
https://aclanthology.org/S19-2142
DOI:
10.18653/v1/S19-2142
Bibkey:
Cite (ACL):
Chengjin Zhou, Jin Wang, and Xuejie Zhang. 2019. YNU-HPCC at SemEval-2019 Task 6: Identifying and Categorising Offensive Language on Twitter. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 812–817, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):
YNU-HPCC at SemEval-2019 Task 6: Identifying and Categorising Offensive Language on Twitter (Zhou et al., SemEval 2019)
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PDF:
https://aclanthology.org/S19-2142.pdf