Cross-Platform Evaluation for Italian Hate Speech Detection

Michele Corazza (1) , Stefano Menini (2) , Elena Cabrio (1) , Sara Tonelli (2) , Serena Villata (1, 3)

1 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
2 FBK - Fondazione Bruno Kessler [Trento, Italy]
3 CNRS - Centre National de la Recherche Scientifique

English. Despite the number of approaches recently proposed in NLP for detecting abusive language on social networks , the issue of developing hate speech detection systems that are robust across different platforms is still an unsolved problem. In this paper we perform a comparative evaluation on datasets for hate speech detection in Italian, extracted from four different social media platforms, i.e. Facebook, Twitter, Instagram and What-sApp. We show that combining such platform-dependent datasets to take advantage of training data developed for other platforms is beneficial, although their impact varies depending on the social network under consideration. 1 Italiano. Nonostante si osservi un cre-scente interesse per approcci che identi-fichino il linguaggio offensivo sui social network attraverso l'NLP, la necessità di sviluppare sistemi che mantengano una buona performance anche su piattaforme diverseè ancora un tema di ricerca aper-to. In questo contributo presentiamo una valutazione comparativa su dataset per l'identificazione di linguaggio d'odio pro-venienti da quattro diverse piattaforme: Facebook, Twitter, Instagram and Wha-tsApp. Lo studio dimostra che, combinan-do dataset diversi per aumentare i dati di training, migliora le performance di clas-sificazione, anche se l'impatto varia a se-conda della piattaforma considerata. 1

Domaines: Informatique

Michele Corazza, Stefano Menini, Elena Cabrio, Sara Tonelli, Serena Villata. Cross-Platform Evaluation for Italian Hate Speech Detection. CLiC-it 2019 - 6th Annual Conference of the Italian Association for Computational Linguistics, Nov 2019, Bari, Italy. ⟨hal-02381152⟩