Comparing Different Supervised Approaches to Hate Speech Detection

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

Risultato della ricerca: Contributo in libroContributo a convegno

1 Citazioni (Scopus)


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.
Lingua originaleEnglish
Titolo della pubblicazione ospiteProceedings of the Sixth Evaluation Campaign of Natural Language processing and Speech Tools for Italian (EVALITA 2018)
Numero di pagine5
Stato di pubblicazionePubblicato - 2018
EventoEVALITA 2018 - Torino, Italy
Durata: 12 dic 201813 dic 2018


WorkshopEVALITA 2018
CittàTorino, Italy


  • hate speech detection, information extraction, Italian


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