The Titans at SemEval-2019 Task 6: Offensive Language Identification, Categorization and Target Identification

Avishek Garain, Arpan Basu


Abstract
This system paper is a description of the system submitted to “SemEval-2019 Task 6”, where we had to detect offensive language in Twitter. There were two specific target audiences, immigrants and women. The language of the tweets was English. We were required to first detect whether a tweet contains offensive content, and then we had to find out whether the tweet was targeted against some individual, group or other entity. Finally we were required to classify the targeted audience.
Anthology ID:
S19-2133
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:
759–762
Language:
URL:
https://aclanthology.org/S19-2133
DOI:
10.18653/v1/S19-2133
Bibkey:
Cite (ACL):
Avishek Garain and Arpan Basu. 2019. The Titans at SemEval-2019 Task 6: Offensive Language Identification, Categorization and Target Identification. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 759–762, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):
The Titans at SemEval-2019 Task 6: Offensive Language Identification, Categorization and Target Identification (Garain & Basu, SemEval 2019)
Copy Citation:
PDF:
https://aclanthology.org/S19-2133.pdf