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.
|Titolo della pubblicazione ospite||Proceedings of the Sixth Evaluation Campaign of Natural Language processing and Speech Tools for Italian (EVALITA 2018)|
|Numero di pagine||5|
|Stato di pubblicazione||Pubblicato - 2018|
|Evento||EVALITA 2018 - Torino, Italy|
Durata: 12 dic 2018 → 13 dic 2018
|Periodo||12/12/18 → 13/12/18|
- hate speech detection, information extraction, Italian