Subjective $\textitIsms$? On the Danger of Conflating Hate and Offence in Abusive Language Detection
<|reference_start|>Subjective $\textitIsms$? On the Danger of Conflating Hate and Offence in Abusive Language Detection: Natural language processing research has begun to embrace the notion of annotator subjectivity, motivated by variations in labelling. This approach understands each annotator's view as valid, which can be highly suitable for tasks that embed subjectivity, e.g., sentiment analysis. However, this construction may be inappropriate for tasks such as hate speech detection, as it affords equal validity to all positions on e.g., sexism or racism. We argue that the conflation of hate and offence can invalidate findings on hate speech, and call for future work to be situated in theory, disentangling hate from its orthogonal concept, offence.<|reference_end|>
@article{curry2024subjective,
    title={Subjective $\textit{Isms}$? On the Danger of Conflating Hate and Offence
  in Abusive Language Detection},
    author={Amanda Cercas Curry, Gavin Abercrombie, Zeerak Talat},
    journal={arXiv preprint arXiv:2403.02268},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.02268},
    primaryClass={cs.CL cs.AI cs.CY}
}