DeepAnalyzer at SemEval-2019 Task 6: A deep learning-based ensemble method for identifying offensive tweets

Gretel Liz De la Peña, Paolo Rosso

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Abstract
This paper describes the system we developed for SemEval 2019 on Identifying and Categorizing Offensive Language in Social Media (OffensEval - Task 6). The task focuses on offensive language in tweets. It is organized into three sub-tasks for offensive language identification; automatic categorization of offense types and offense target identification. The approach for the first subtask is a deep learning-based ensemble method which uses a Bidirectional LSTM Recurrent Neural Network and a Convolutional Neural Network. Additionally we use the information from part-of-speech tagging of tweets for target identification and combine previous results for categorization of offense types.
Anthology ID:
S19-2104
Volume:
Proceedings of the 13th International Workshop on Semantic Evaluation
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota, USA
Editors:
Jonathan May, Ekaterina Shutova, Aurelie Herbelot, Xiaodan Zhu, Marianna Apidianaki, Saif M. Mohammad
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
582–586
Language:
URL:
https://aclanthology.org/S19-2104
DOI:
10.18653/v1/S19-2104
Bibkey:
Cite (ACL):
Gretel Liz De la Peña and Paolo Rosso. 2019. DeepAnalyzer at SemEval-2019 Task 6: A deep learning-based ensemble method for identifying offensive tweets. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 582–586, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):
DeepAnalyzer at SemEval-2019 Task 6: A deep learning-based ensemble method for identifying offensive tweets (De la Peña & Rosso, SemEval 2019)
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PDF:
https://preview.aclanthology.org/teach-a-man-to-fish/S19-2104.pdf
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