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InriaFBK at Germeval 2018: Identifying Offensive Tweets Using Recurrent Neural Networks

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

Risultato della ricerca: Contributo in libroContributo a conferenza

Abstract

In this paper, we describe two systems for predicting message-level offensive language in German tweets: one discriminates between offensive and not offensive messages, and the second performs a fine-grained classification by recognizing also classes of offense. Both systems are based on the same approach, which builds upon Recurrent Neural Networks used with the following features: word embeddings, emoji embeddings and social-network specific features. The model is able to combine word-level information and tweet-level information in order to perform the classification tasks.
Lingua originaleInglese
Titolo della pubblicazione ospiteProceedings of the GermEval 2018 Workshop
Pagine80-84
Numero di pagine5
Stato di pubblicazionePubblicato - 2018
EventoGermEval 2018 - Vienna, Austria
Durata: 21 dic 201821 dic 2018

Workshop

WorkshopGermEval 2018
CittàVienna, Austria
Periodo21/12/1821/12/18

Keywords

  • hate speech detection, neural networks, evaluation campaign

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