Abstract
This paper presents a detailed description of our participation in task 5 on SemEval-2019. This task consists of classifying English and Spanish tweets that contain hate towards women or immigrants. We carried out several experiments; for a finer-grained study of the task, we analyzed different features and designing architectures of neural networks. Additionally, to face the lack of hate content in tweets, we include data augmentation as a technique to in- crease hate content in our datasets.- Anthology ID:
- S19-2072
- 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:
- 409–415
- Language:
- URL:
- https://aclanthology.org/S19-2072
- DOI:
- 10.18653/v1/S19-2072
- Cite (ACL):
- Victor Nina-Alcocer. 2019. HATERecognizer at SemEval-2019 Task 5: Using Features and Neural Networks to Face Hate Recognition. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 409–415, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
- Cite (Informal):
- HATERecognizer at SemEval-2019 Task 5: Using Features and Neural Networks to Face Hate Recognition (Nina-Alcocer, SemEval 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/S19-2072.pdf