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Autores principales: Wang, Luna, Caines, Andrew, Hutchings, Alice
Formato: Preprint
Publicado: 2025
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Acceso en línea:https://arxiv.org/abs/2506.16190
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author Wang, Luna
Caines, Andrew
Hutchings, Alice
author_facet Wang, Luna
Caines, Andrew
Hutchings, Alice
contents The curation of hate speech datasets involves complex design decisions that balance competing priorities. This paper critically examines these methodological choices in a diverse range of datasets, highlighting common themes and practices, and their implications for dataset reliability. Drawing on Max Weber's notion of ideal types, we argue for a reflexive approach in dataset creation, urging researchers to acknowledge their own value judgments during dataset construction, fostering transparency and methodological rigour.
format Preprint
id arxiv_https___arxiv_org_abs_2506_16190
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Web(er) of Hate: A Survey on How Hate Speech Is Typed
Wang, Luna
Caines, Andrew
Hutchings, Alice
Computation and Language
The curation of hate speech datasets involves complex design decisions that balance competing priorities. This paper critically examines these methodological choices in a diverse range of datasets, highlighting common themes and practices, and their implications for dataset reliability. Drawing on Max Weber's notion of ideal types, we argue for a reflexive approach in dataset creation, urging researchers to acknowledge their own value judgments during dataset construction, fostering transparency and methodological rigour.
title Web(er) of Hate: A Survey on How Hate Speech Is Typed
topic Computation and Language
url https://arxiv.org/abs/2506.16190