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NAYEL @LT-EDI-ACL2022: Homophobia/Transphobia Detection for Equality, Diversity, and Inclusion using SVM

Article scientifique 2022 Anglais

Résumé

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 models for vectorization of comments. Support Vector Machines have been used to develop the proposed model and our submission reported 0.91, 0.92, 0.88 weighted F1-scores for English, Tamil and Tamil-English datasets respectively.

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Ashraf, N., Taha, A., Elfattah, A., Nayel, H. (2022). NAYEL @LT-EDI-ACL2022: Homophobia/Transphobia Detection for Equality, Diversity, and Inclusion using SVM. https://doi.org/10.18653/v1/2022.ltedi-1.42

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Auteur(s)

Nsrin Ashraf Ahmed Taha Ahmed Abd Elfattah Hamada Nayel

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