Comparing Different Supervised Approaches to Hate Speech Detection

Michele Corazza, Stefano Menini, Pinar Arslan, Rachele Sprugnoli, Elena Cabrio, Sara Tonelli, Serena Villata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper reports on the systems the InriaFBK Team submitted to the EVALITA 2018 - Shared Task on Hate Speech Detection in Italian Twitter and Facebook posts (HaSpeeDe). Our submissions were based on three separate classes of models: a model using a recurrent layer, an ngram-based neural network and a LinearSVC. For the Facebook task and the two cross-domain tasks we used the recurrent model and obtained promising results, especially in the cross-domain setting. For Twitter, we used an ngram-based neural network and the LinearSVC-based model.
Original languageEnglish
Title of host publicationProceedings of the Sixth Evaluation Campaign of Natural Language processing and Speech Tools for Italian (EVALITA 2018)
Pages230-234
Number of pages5
Volume2263
DOIs
Publication statusPublished - 2018
Event6th Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop, EVALITA 2018 - Torino, Italy
Duration: 12 Dec 201813 Dec 2018

Publication series

NameCEUR WORKSHOP PROCEEDINGS

Workshop

Workshop6th Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop, EVALITA 2018
CityTorino, Italy
Period12/12/1813/12/18

Keywords

  • hate speech detection, information extraction, Italian

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