Web(er) of Hate: A Survey on How Hate Speech Is Typed
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866909653063958528 |
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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 |