IMT Mines Ales at HASOC 2019: Automatic Hate Speech Detection
| Autor: | Jean-Christophe Mensonides, Pierre-Antoine Jean, Andon Tchechmedjiev, Sébastien Harispe |
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| Přispěvatelé: | Laboratoire de Génie Informatique et Ingénierie de Production (LGI2P), IMT - MINES ALES (IMT - MINES ALES), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), IMT - Mines Alès, Administrateur |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | FIRE 2019-11th Forum for Information Retrieval Evaluation FIRE 2019-11th Forum for Information Retrieval Evaluation, Dec 2019, Kolkata, India. p.279-284 HAL |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
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