Coco at SemEval-2023 Task 10: Explainable Detection of Online Sexism

Kangshuai Guo, Ruipeng Ma, Shichao Luo, Yan Wang

Abstract
Sexism has become a growing concern on social media platforms as it impacts the health of the internet and can have negative impacts on society. This paper describes the coco system that participated in SemEval-2023 Task 10, Explainable Detection of Online Sexism (EDOS), which aims at sexism detection in various settings of natural language understanding. We develop a novel neural framework for sexism detection and misogyny that can combine text representations obtained using pre-trained language model models such as Bidirectional Encoder Representations from Transformers and using BiLSTM architecture to obtain the local and global semantic information. Further, considering that the EDOS dataset is relatively small and extremely unbalanced, we conducted data augmentation and introduced two datasets in the field of sexism detection. Moreover, we introduced Focal Loss which is a loss function in order to improve the performance of processing imbalanced data classification. Our system achieved an F1 score of 78.95\% on Task A - binary sexism.
Anthology ID:
2023.semeval-1.65
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:
469–476
Language:
URL:
https://aclanthology.org/2023.semeval-1.65
DOI:
10.18653/v1/2023.semeval-1.65
Bibkey:
Cite (ACL):
Kangshuai Guo, Ruipeng Ma, Shichao Luo, and Yan Wang. 2023. Coco at SemEval-2023 Task 10: Explainable Detection of Online Sexism. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 469–476, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
Coco at SemEval-2023 Task 10: Explainable Detection of Online Sexism (Guo et al., SemEval 2023)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-1/2023.semeval-1.65.pdf
PDF Search