ACSMKRHR at SemEval-2023 Task 10: Explainable Online Sexism Detection(EDOS)

Rakib Hossain Rifat, Abanti Shruti, Marufa Kamal, Farig Sadeque

Abstract
People are expressing their opinions online for a lot of years now. Although these opinions and comments provide people an opportunity of expressing their views, there is a lot of hate speech that can be found online. More specifically, sexist comments are very popular affecting and creating a negative impact on a lot of women and girls online. This paper describes the approaches of the SemEval-2023 Task 10 competition for Explainable Online Sexism Detection (EDOS). The task has been divided into 3 subtasks, introducing different classes of sexist comments. We have approached these tasks using the bert-cased and uncased models which are trained on the annotated dataset that has been provided in the competition. Task A provided the best F1 score of 80% on the test set, and tasks B and C provided 58% and 40% respectively.
Anthology ID:
2023.semeval-1.99
Volume:
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
724–732
Language:
URL:
https://aclanthology.org/2023.semeval-1.99
DOI:
10.18653/v1/2023.semeval-1.99
Bibkey:
Cite (ACL):
Rakib Hossain Rifat, Abanti Shruti, Marufa Kamal, and Farig Sadeque. 2023. ACSMKRHR at SemEval-2023 Task 10: Explainable Online Sexism Detection(EDOS). In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 724–732, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
ACSMKRHR at SemEval-2023 Task 10: Explainable Online Sexism Detection(EDOS) (Rifat et al., SemEval 2023)
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PDF:
https://preview.aclanthology.org/dois-2013-emnlp/2023.semeval-1.99.pdf
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