Abstract
Hateful and offensive content on social media platforms can have negative effects on users and can make online communities more hostile towards certain people and hamper equality, diversity and inclusion. In this paper, we describe our approach to classify homophobia and transphobia in social media comments. We used an ensemble of transformer-based models to build our classifier. Our model ranked 2nd for English, 8th for Tamil and 10th for Tamil-English.- Anthology ID:
- 2022.ltedi-1.39
- Volume:
- Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion
- Month:
- May
- Year:
- 2022
- Address:
- Dublin, Ireland
- Editors:
- Bharathi Raja Chakravarthi, B Bharathi, John P McCrae, Manel Zarrouk, Kalika Bali, Paul Buitelaar
- Venue:
- LTEDI
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 270–275
- Language:
- URL:
- https://aclanthology.org/2022.ltedi-1.39
- DOI:
- 10.18653/v1/2022.ltedi-1.39
- Cite (ACL):
- Ishan Sanjeev Upadhyay, Kv Aditya Srivatsa, and Radhika Mamidi. 2022. Sammaan@LT-EDI-ACL2022: Ensembled Transformers Against Homophobia and Transphobia. In Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion, pages 270–275, Dublin, Ireland. Association for Computational Linguistics.
- Cite (Informal):
- Sammaan@LT-EDI-ACL2022: Ensembled Transformers Against Homophobia and Transphobia (Upadhyay et al., LTEDI 2022)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2022.ltedi-1.39.pdf
- Data
- GLUE