JCTICOL at SemEval-2019 task 6: Classifying offensive language in social media using deep learning methods, word/character N-gram features, and preprocessing methods

Yaakov HaCohen-Kerner; Ziv Ben-David; Gal Didi; Eli Cahn; Shalom Rochman; Elyashiv Shayovitz

JCTICOL at SemEval-2019 task 6: Classifying offensive language in social media using deep learning methods, word/character N-gram features, and preprocessing methods

Yaakov HaCohen-Kerner, Ziv Ben-David, Gal Didi, Eli Cahn, Shalom Rochman, Elyashiv Shayovitz

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

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 ngram 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 25^th position out of 65 submissions for the most complex sub-task (C).

Original language	English
Title of host publication	NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop
Publisher	Association for Computational Linguistics (ACL)
Pages	645-651
Number of pages	7
ISBN (Electronic)	9781950737062
State	Published - 2019
Externally published	Yes
Event	13th International Workshop on Semantic Evaluation, SemEval 2019, co-located with the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019 - Minneapolis, United States Duration: 6 Jun 2019 → 7 Jun 2019

Publication series

Name	NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop

Conference

Conference	13th International Workshop on Semantic Evaluation, SemEval 2019, co-located with the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019
Country/Territory	United States
City	Minneapolis
Period	6/06/19 → 7/06/19

Bibliographical note

Funding Information:
This research was partially funded by the Jerusalem College of Technology, Lev Academic Center.

Publisher Copyright:
© 2019 Association for Computational Linguistics

Cite this

HaCohen-Kerner, Y., Ben-David, Z., Didi, G., Cahn, E., Rochman, S., & Shayovitz, E. (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 NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop (pp. 645-651). (NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop). Association for Computational Linguistics (ACL).

HaCohen-Kerner, Yaakov ; Ben-David, Ziv ; Didi, Gal et al. / JCTICOL at SemEval-2019 task 6 : Classifying offensive language in social media using deep learning methods, word/character N-gram features, and preprocessing methods. NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop. Association for Computational Linguistics (ACL), 2019. pp. 645-651 (NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop).

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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",

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 ngram 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).",

author = "Yaakov HaCohen-Kerner and Ziv Ben-David and Gal Didi and Eli Cahn and Shalom Rochman and Elyashiv Shayovitz",

note = "Publisher Copyright: {\textcopyright} 2019 Association for Computational Linguistics; 13th International Workshop on Semantic Evaluation, SemEval 2019, co-located with the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019 ; Conference date: 06-06-2019 Through 07-06-2019",

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publisher = "Association for Computational Linguistics (ACL)",

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HaCohen-Kerner, Y, Ben-David, Z, Didi, G, Cahn, E, Rochman, S & Shayovitz, E 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 NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop. NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop, Association for Computational Linguistics (ACL), pp. 645-651, 13th International Workshop on Semantic Evaluation, SemEval 2019, co-located with the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019, Minneapolis, United States, 6/06/19.

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, Yaakov; Ben-David, Ziv; Didi, Gal et al.
NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop. Association for Computational Linguistics (ACL), 2019. p. 645-651 (NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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HaCohen-Kerner Y, Ben-David Z, Didi G, Cahn E, Rochman S, Shayovitz E. 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 NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop. Association for Computational Linguistics (ACL). 2019. p. 645-651. (NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop).

JCTICOL at SemEval-2019 task 6: Classifying offensive language in social media using deep learning methods, word/character N-gram features, and preprocessing methods

Abstract

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Bibliographical note

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