NAYEL @LT-EDI-ACL2022: Homophobia/Transphobia Detection for Equality, Diversity, and Inclusion using SVM
Nsrin Ashraf, Mohamed Taha, Ahmed Abd Elfattah, Hamada Nayel
Abstract
Analysing the contents of social media platforms such as YouTube, Facebook and Twitter gained interest due to the vast number of users. One of the important tasks is homophobia/transphobia detection. This paper illustrates the system submitted by our team for the homophobia/transphobia detection in social media comments shared task. A machine learning-based model has been designed and various classification algorithms have been implemented for automatic detection of homophobia in YouTube comments. TF/IDF has been used with a range of bigram model for vectorization of comments. Support Vector Machines has been used to develop the proposed model and our submission reported 0.91, 0.92, 0.88 weighted f1-score for English, Tamil and Tamil-English datasets respectively.- Anthology ID:
- 2022.ltedi-1.42
- Volume:
- Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion
- Month:
- May
- Year:
- 2022
- Address:
- Dublin, Ireland
- Venue:
- LTEDI
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 287–290
- Language:
- URL:
- https://aclanthology.org/2022.ltedi-1.42
- DOI:
- 10.18653/v1/2022.ltedi-1.42
- Cite (ACL):
- Nsrin Ashraf, Mohamed Taha, Ahmed Abd Elfattah, and Hamada Nayel. 2022. NAYEL @LT-EDI-ACL2022: Homophobia/Transphobia Detection for Equality, Diversity, and Inclusion using SVM. In Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion, pages 287–290, Dublin, Ireland. Association for Computational Linguistics.
- Cite (Informal):
- NAYEL @LT-EDI-ACL2022: Homophobia/Transphobia Detection for Equality, Diversity, and Inclusion using SVM (Ashraf et al., LTEDI 2022)
- PDF:
- https://preview.aclanthology.org/starsem-semeval-split/2022.ltedi-1.42.pdf