@inproceedings{lommel-etal-2025-beyond,
title = "Beyond Negative Stereotypes {--} Non-Negative Abusive Utterances about Identity Groups and Their Semantic Variants",
author = "Lommel, Tina and
Eder, Elisabeth and
Ruppenhofer, Josef and
Wiegand, Michael",
editor = "Che, Wanxiang and
Nabende, Joyce and
Shutova, Ekaterina and
Pilehvar, Mohammad Taher",
booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.acl-long.1363/",
doi = "10.18653/v1/2025.acl-long.1363",
pages = "28102--28120",
ISBN = "979-8-89176-251-0",
abstract = "We study a subtype of implicitly abusive language, namely non-negative sentences about identity groups (e.g. ``Women make good cooks''), and introduce a novel dataset of such utterances. Not only do we profile such abusive sentences, but since our dataset includes different semantic variants of the same characteristic attributed to an identity group, we can also systematically study the impact of varying degrees of generalization and perspective framing. Similarly, we switch identity groups to assess whether the characteristic described in a sentence is inherently abusive. We also report on classification experiments."
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<abstract>We study a subtype of implicitly abusive language, namely non-negative sentences about identity groups (e.g. “Women make good cooks”), and introduce a novel dataset of such utterances. Not only do we profile such abusive sentences, but since our dataset includes different semantic variants of the same characteristic attributed to an identity group, we can also systematically study the impact of varying degrees of generalization and perspective framing. Similarly, we switch identity groups to assess whether the characteristic described in a sentence is inherently abusive. We also report on classification experiments.</abstract>
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%0 Conference Proceedings
%T Beyond Negative Stereotypes – Non-Negative Abusive Utterances about Identity Groups and Their Semantic Variants
%A Lommel, Tina
%A Eder, Elisabeth
%A Ruppenhofer, Josef
%A Wiegand, Michael
%Y Che, Wanxiang
%Y Nabende, Joyce
%Y Shutova, Ekaterina
%Y Pilehvar, Mohammad Taher
%S Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-251-0
%F lommel-etal-2025-beyond
%X We study a subtype of implicitly abusive language, namely non-negative sentences about identity groups (e.g. “Women make good cooks”), and introduce a novel dataset of such utterances. Not only do we profile such abusive sentences, but since our dataset includes different semantic variants of the same characteristic attributed to an identity group, we can also systematically study the impact of varying degrees of generalization and perspective framing. Similarly, we switch identity groups to assess whether the characteristic described in a sentence is inherently abusive. We also report on classification experiments.
%R 10.18653/v1/2025.acl-long.1363
%U https://aclanthology.org/2025.acl-long.1363/
%U https://doi.org/10.18653/v1/2025.acl-long.1363
%P 28102-28120
Markdown (Informal)
[Beyond Negative Stereotypes – Non-Negative Abusive Utterances about Identity Groups and Their Semantic Variants](https://aclanthology.org/2025.acl-long.1363/) (Lommel et al., ACL 2025)
ACL