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BiaSWE: An Expert Annotated Dataset for Misogyny Detection in Swedish

arXiv 2502.07637 ↗First posted 11 Feb 2025cs.CLcited by 0

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Abstract (arXiv)

In this study, we introduce the process for creating BiaSWE, an expert-annotated dataset tailored for misogyny detection in the Swedish language. To address the cultural and linguistic specificity of misogyny in Swedish, we collaborated with experts from the social sciences and humanities. Our interdisciplinary team developed a rigorous annotation process, incorporating both domain knowledge and language expertise, to capture the nuances of misogyny in a Swedish context. This methodology ensures that the dataset is not only culturally relevant but also aligned with broader efforts in bias detection for low-resource languages. The dataset, along with the annotation guidelines, is publicly available for further research.

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  1. 2021Stakeholder Participation in AI: Beyond "Add Diverse Stakeholders and Stir"cited by 26

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