LaSTUS/TALN at SemEval-2019 task 6: identification and categorization of offensive language in social media with attention-based Bi-LSTM model
LaSTUS/TALN at SemEval-2019 task 6: identification and categorization of offensive language in social media with attention-based Bi-LSTM model
Citació
- Altin LSM, Bravo A, Saggion H. LaSTUS/TALN at SemEval-2019 task 6: identification and categorization of offensive language in social media with attention-based Bi-LSTM model. In: Proceedings of the 13th International Workshop on Semantic Evaluation, NAACL HLT 2019; 2019 June 6-7; Minneapolis, United States of America. Stroudsburg: The Association for Computational Linguistics;2019. p. 672-7.
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Descripció
Resum
This paper describes a bidirectional LongShort Term Memory network for identifying offensive language in Twitter. Our system has been developed in the context of the SemEval 2019 Task 6 which comprises three different sub-tasks, namely A: Offensive Language Detection, B: Categorization of Offensive Language, C: Offensive Language Target Identification. We used a pre-trained Word Embeddings in tweet data, including information about emojis and hashtags. Our approach achieves good performance in the three subtasks.Descripció
Comunicació presentada a: 13th International Workshop on Semantic Evaluation, NAACL HLT 2019, celebrat del 6 al 7 de juny de 2019, a Minneapolis, Estats Units d'Amèrica.