Abstract
This paper describes our system designed for SemEval 2019 Task 5 “Shared Task on Multilingual Detection of Hate”.We only participate in subtask-A in English. To address this task, we present a stacked BiGRU model based on a capsule network system. In or- der to convert the tweets into corresponding vector representations and input them into the neural network, we use the fastText tools to get word representations. Then, the sentence representation is enriched by stacked Bidirectional Gated Recurrent Units (BiGRUs) and used as the input of capsule network. Our system achieves an average F1-score of 0.546 and ranks 3rd in the subtask-A in English.- Anthology ID:
- S19-2096
- Volume:
- Proceedings of the 13th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2019
- Address:
- Minneapolis, Minnesota, USA
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 535–539
- Language:
- URL:
- https://aclanthology.org/S19-2096
- DOI:
- 10.18653/v1/S19-2096
- Cite (ACL):
- Yunxia Ding, Xiaobing Zhou, and Xuejie Zhang. 2019. YNU_DYX at SemEval-2019 Task 5: A Stacked BiGRU Model Based on Capsule Network in Detection of Hate. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 535–539, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
- Cite (Informal):
- YNU_DYX at SemEval-2019 Task 5: A Stacked BiGRU Model Based on Capsule Network in Detection of Hate (Ding et al., SemEval 2019)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/S19-2096.pdf