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Communication Dans Un Congrès Année : 2019

IMT Mines Ales at HASOC 2019: Automatic Hate Speech Detection

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Résumé

This paper presents the contribution of the LGI2P (Labo-ratoire de Génie Informatique et d'Ingénierie de Production) team from IMT Mines Alès to the Hate Speech and Offensive Content Identification in Indo-European Languages (HASOC) 2019 shared task. This challenge aims at automatically identifying hate speech content in social media through three sub-tasks, each available in three different languages (En-glish, German and Hindi). We are interested in sub-tasks A and B, requiring to (A) classify tweets as offensive or as non offensive, and (B) to further classify offensive tweets from sub-task A as hate speech, offensive speech or profane. We trained a fastText model for each proposed language and obtained promising results on the Hindi dataset for both sub-tasks A and B.
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Dates et versions

hal-02427843 , version 1 (04-01-2020)

Identifiants

  • HAL Id : hal-02427843 , version 1

Citer

Jean-Christophe Mensonides, Pierre-Antoine Jean, Andon Tchechmedjiev, Sébastien Harispe. IMT Mines Ales at HASOC 2019: Automatic Hate Speech Detection. FIRE 2019 - 11th Forum for Information Retrieval Evaluation, Dec 2019, Kolkata, India. p.279-284. ⟨hal-02427843⟩
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