HurtLens: A Perspectivist Corpus Analysis of Hurtful Language

Samuele D’Avenia, Eliana Di Palma, Marta Marchiori Manerba, Valerio Basile


Abstract
Offensive language detection systems often rely on majority-aggregated annotations, overlooking the diversity of perspectives that shape how different communities perceive harm. In this contribution, we introduce HurtLens, a perspectivist corpus of hurtful language leveraging four disaggregated datasets which are automatically enriched through HurtLex lemmas, a multilingual resource of offensive and derogatory terms. Using mixed-effects modeling, we investigate how annotators’ sociodemographic backgrounds, the presence of specific types of offensive language (through Hurtlex categories) and their interaction influence offensiveness ratings. Our analysis reveals that offensiveness ratings are influenced both by annotators’ sociodemographic characteristics (particularly when considering them in intersection) and by the presence of specific types of offensive language. Additionally, we identify significant interaction effects showing that different demographic groups vary in their sensitivity to texts containing particular types of offensive language.
Anthology ID:
2026.nlperspectives-1.5
Volume:
Proceedings of the the fifth edition of NLPerspectives
Month:
May
Year:
2026
Address:
Palma, Mallorca (Spain)
Editors:
Shiran Dudy, Gavin Abercrombie, Valerio Basile, Elisa Leonardelli, Simona Frenda
Venues:
NLPerspectives | WS
SIG:
Publisher:
ELRA Language Resources Association (ELRA)
Note:
Pages:
44–55
Language:
External URL:
https://lrec.elra.info/lrec2026-ws-nlperspectives-05
DOI:
10.63317/483mhsjprvmo
Bibkey:
Cite (ACL):
Samuele D’Avenia, Eliana Di Palma, Marta Marchiori Manerba, and Valerio Basile. 2026. HurtLens: A Perspectivist Corpus Analysis of Hurtful Language. In Proceedings of the the fifth edition of NLPerspectives, pages 44–55, Palma, Mallorca (Spain). ELRA Language Resources Association (ELRA).
Cite (Informal):
HurtLens: A Perspectivist Corpus Analysis of Hurtful Language (D’Avenia et al., NLPerspectives 2026)
Copy Citation: