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11 mai 2021
- doi: 10.4000/books.aaccademia.7037
- eisbn: 9791280136329
https://creativecommons.org/licenses/by-nc-nd/4.0/ , info:eu-repo/semantics/openAccess
Mots-clés
EVALITA COVID-19 Infodemic linguistica computazionale Automatic Misogyny Identification Misogyny on Twitter Posts AlBERTo Convolutional Neural Network BERT Model Hate Speech Detection Multimodal Meme Detection MEME management Language Game ``La Ghigliottina'' Language & Linguistics LAN000000 CBXSujets proches
Speech, Hate Group libel Group defamation Defamation against groups Racist speech Pattern ModelCiter ce document
Svea Klaus et al., « Svandiela @ HaSpeeDe: Detecting Hate Speech in Italian Twitter Data with BERT », Accademia University Press, ID : 10.4000/books.aaccademia.7037
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Résumé
This paper explains the system developed for the Hate Speech Detection (HaSpeeDe) shared task within the 7th evaluation campaign EVALITA 2020 (Basile et al. 2020). The task solution proposed in this work is based on a fine-tuned BERT model. In cross-corpus evaluation, our model reached an F1 score of 77,56% on the tweets test set, and 60,31% on the news headlines test set.