User-based Evaluation of Explainability Techniques for Misogyny Detection in Code-mixed Hindi-English

Although Artificial Intelligence (AI) models have demonstrated great success and efficiency in automatically countering online hate speech and misogyny, they suffer from a lack of explainability and transparency. Explainable Artificial Intelligence (X

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Publication Details

Published
2025-09-22
DOI
https://doi.org/10.22541/au.175856176.63643017/v1
Primary Topic
Hate Speech and Cyberbullying Detection
Type
article
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article

User-based Evaluation of Explainability Techniques for Misogyny Detection in Code-mixed Hindi-English

Sargam Yadav, Kevin McDaid, Abhishek Kaushik
Hate Speech and Cyberbullying Detection
article

User-based Evaluation of Explainability Techniques for Misogyny Detection in Code-mixed Hindi-English

Sargam Yadav, Kevin McDaid, Abhishek Kaushik
article en

Abstract

Although Artificial Intelligence (AI) models have demonstrated great success and efficiency in automatically countering online hate speech and misogyny, they suffer from a lack of explainability and transparency. Explainable Artificial Intelligence (X

Dundalk Institute of Technology (IE)
Openalex Percentile: Top 86%
Hate Speech and Cyberbullying Detection
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User-based Evaluation of Explainability Techniques for Misogyny Detection in Code-mixed Hindi-English — Sargam Yadav, Kevin McDaid, et al. · (2025) | TGRS Research Map | TGRS