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Communication Dans Un Congrès Année : 2018

Comparing Different Supervised Approaches to Hate Speech Detection

Résumé

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.
Questo articolo descrive i modelli del team InriaFBK per lo Shared Task on Hate Speech Detection in Italian Twitter and Facebook posts (HaSpeeDe) di EVALITA 2018. Tre classi di modelli differenti sono state utilizzate: un model-lo che usa un livello ricorrente, una rete neurale basata su ngrammi e un modello basato su LinearSVC. Per Facebook e i due task cross-domain, sì e scelto un modello ricorrente che ha ottenuto buoni risultati, specialmente per quanto riguarda i task cross-domain. Per Twitter, sono stati utilizzati la rete neurale basata su ngrammi e il modello basato su LinearSVC.
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Dates et versions

hal-01920266 , version 1 (13-11-2018)

Identifiants

  • HAL Id : hal-01920266 , version 1

Citer

Michele Corazza, Stefano Menini, Pinar Arslan, Rachele Sprugnoli, Elena Cabrio, et al.. Comparing Different Supervised Approaches to Hate Speech Detection. EVALITA 2018, Dec 2018, Turin, Italy. ⟨hal-01920266⟩
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