Subjective $\textit{Isms}$? On the Danger of Conflating Hate and Offence in Abusive Language Detection

Fuente: arXiv
Guardado en:
Detalles Bibliográficos
Autores principales: Curry, Amanda Cercas, Abercrombie, Gavin, Talat, Zeerak
Formato: Preprint
Publicado: 2024
Materias:
Acceso en línea:
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866910353411014656
author Curry, Amanda Cercas
Abercrombie, Gavin
Talat, Zeerak
author_facet Curry, Amanda Cercas
Abercrombie, Gavin
Talat, Zeerak
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2403_02268
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Subjective $\textit{Isms}$? On the Danger of Conflating Hate and Offence in Abusive Language Detection
Curry, Amanda Cercas
Abercrombie, Gavin
Talat, Zeerak
Computation and Language
Artificial Intelligence
Computers and Society
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.
title Subjective $\textit{Isms}$? On the Danger of Conflating Hate and Offence in Abusive Language Detection
topic Computation and Language
Artificial Intelligence
Computers and Society
url https://arxiv.org/abs/2403.02268