Fiche du document
5 juin 2019
- doi: 10.4000/books.aaccademia.4698
- isbn: 9788831978422
- eisbn: 9788831978699
https://creativecommons.org/licenses/by-nc-nd/4.0/ , info:eu-repo/semantics/openAccess
Mots-clés
elaborazione del linguaggio naturale strumenti del linguaggio traitement du langage naturel outils du langage Natural Language Processing Speech Tools Language & Linguistics LAN009000 CFSujets proches
Language (New words, slang, etc.) Speech, Hate Group libel Group defamation Defamation against groups Racist speech User-generated mediaCiter ce document
Resham Ahluwalia et al., « Detecting Hate Speech Against Women in English Tweets », Accademia University Press, ID : 10.4000/books.aaccademia.4698
Métriques
Partage / Export
Résumé
Hate speech is prevalent in social media platforms. Systems that can automatically detect offensive content are of great value to assist human curators with removal of hateful language. In this paper, we present machine learning models developed at UW Tacoma for detection of misogyny, i.e. hate speech against women, in English tweets, and the results obtained with these models in the shared task for Automatic Misogyny Identification (AMI) at EVALITA2018.