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        <title>JCTICOL at SemEval-2019 Task 6: Classifying Offensive Language in Social Media using Deep Learning Methods, Word/Character N-gram Features, and Preprocessing Methods</title>
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    <abstract>In this paper, we describe our submissions to SemEval-2019 task 6 contest. We tackled all three sub-tasks in this task “OffensEval - Identifying and Categorizing Offensive Language in Social Media”. In our system called JCTICOL (Jerusalem College of Technology Identifies and Categorizes Offensive Language), we applied various supervised ML methods. We applied various combinations of word/character n-gram features using the TF-IDF scheme. In addition, we applied various combinations of seven basic preprocessing methods. Our best submission, an RNN model was ranked at the 25th position out of 65 submissions for the most complex sub-task (C).</abstract>
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%0 Conference Proceedings
%T JCTICOL at SemEval-2019 Task 6: Classifying Offensive Language in Social Media using Deep Learning Methods, Word/Character N-gram Features, and Preprocessing Methods
%A HaCohen-Kerner, Yaakov
%A Ben-David, Ziv
%A Didi, Gal
%A Cahn, Eli
%A Rochman, Shalom
%A Shayovitz, Elyashiv
%S Proceedings of the 13th International Workshop on Semantic Evaluation
%D 2019
%8 jun
%I Association for Computational Linguistics
%C Minneapolis, Minnesota, USA
%F hacohen-kerner-etal-2019-jcticol
%X In this paper, we describe our submissions to SemEval-2019 task 6 contest. We tackled all three sub-tasks in this task “OffensEval - Identifying and Categorizing Offensive Language in Social Media”. In our system called JCTICOL (Jerusalem College of Technology Identifies and Categorizes Offensive Language), we applied various supervised ML methods. We applied various combinations of word/character n-gram features using the TF-IDF scheme. In addition, we applied various combinations of seven basic preprocessing methods. Our best submission, an RNN model was ranked at the 25th position out of 65 submissions for the most complex sub-task (C).
%R 10.18653/v1/S19-2115
%U https://aclanthology.org/S19-2115
%U https://doi.org/10.18653/v1/S19-2115
%P 645-651

Markdown (Informal)

[JCTICOL at SemEval-2019 Task 6: Classifying Offensive Language in Social Media using Deep Learning Methods, Word/Character N-gram Features, and Preprocessing Methods](https://aclanthology.org/S19-2115) (HaCohen-Kerner et al., SemEval 2019)

• JCTICOL at SemEval-2019 Task 6: Classifying Offensive Language in Social Media using Deep Learning Methods, Word/Character N-gram Features, and Preprocessing Methods (HaCohen-Kerner et al., SemEval 2019)

ACL

• Yaakov HaCohen-Kerner, Ziv Ben-David, Gal Didi, Eli Cahn, Shalom Rochman, and Elyashiv Shayovitz. 2019. JCTICOL at SemEval-2019 Task 6: Classifying Offensive Language in Social Media using Deep Learning Methods, Word/Character N-gram Features, and Preprocessing Methods. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 645–651, Minneapolis, Minnesota, USA. Association for Computational Linguistics.