Sarcasm detection on twitter:A behavioral modeling approach

Ashwin Rajadesingan; Reza Zafarani; Huan Liu

doi:10.1145/2684822.2685316

Sarcasm detection on twitter:A behavioral modeling approach

Ashwin Rajadesingan, Reza Zafarani, Huan Liu

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

300 Scopus citations

Abstract

Sarcasm is a nuanced form of language in which individuals state the opposite of what is implied. With this intentional ambiguity, sarcasm detection has always been a challenging task, even for humans. Current approaches to automatic sarcasm detection rely primarily on lexical and linguistic cues. This paper aims to address the di-cult task of sarcasm detection on Twitter by leveraging behavioral traits intrinsic to users expressing sarcasm. We identify such traits using the user's past tweets. We employ theories from behavioral and psychological studies to construct a behavioral modeling framework tuned for detecting sarcasm. We evaluate our framework and demonstrate its efficiency in identifying sarcastic tweets.

Original language	English (US)
Title of host publication	WSDM 2015 - Proceedings of the 8th ACM International Conference on Web Search and Data Mining
Publisher	Association for Computing Machinery
Pages	97-106
Number of pages	10
ISBN (Electronic)	9781450333177
DOIs	https://doi.org/10.1145/2684822.2685316
State	Published - Feb 2 2015
Event	8th ACM International Conference on Web Search and Data Mining, WSDM 2015 - Shanghai, China Duration: Jan 31 2015 → Feb 6 2015

Publication series

Name	WSDM 2015 - Proceedings of the 8th ACM International Conference on Web Search and Data Mining

Other

Other	8th ACM International Conference on Web Search and Data Mining, WSDM 2015
Country/Territory	China
City	Shanghai
Period	1/31/15 → 2/6/15

Keywords

Behavioral modeling
Sarcasm detection
Social media

ASJC Scopus subject areas

Computer Networks and Communications

Access to Document

10.1145/2684822.2685316

Cite this

Rajadesingan, A., Zafarani, R., & Liu, H. (2015). Sarcasm detection on twitter:A behavioral modeling approach. In WSDM 2015 - Proceedings of the 8th ACM International Conference on Web Search and Data Mining (pp. 97-106). (WSDM 2015 - Proceedings of the 8th ACM International Conference on Web Search and Data Mining). Association for Computing Machinery. https://doi.org/10.1145/2684822.2685316

Sarcasm detection on twitter:A behavioral modeling approach. / Rajadesingan, Ashwin; Zafarani, Reza; Liu, Huan.
WSDM 2015 - Proceedings of the 8th ACM International Conference on Web Search and Data Mining. Association for Computing Machinery, 2015. p. 97-106 (WSDM 2015 - Proceedings of the 8th ACM International Conference on Web Search and Data Mining).

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

Rajadesingan, A, Zafarani, R & Liu, H 2015, Sarcasm detection on twitter:A behavioral modeling approach. in WSDM 2015 - Proceedings of the 8th ACM International Conference on Web Search and Data Mining. WSDM 2015 - Proceedings of the 8th ACM International Conference on Web Search and Data Mining, Association for Computing Machinery, pp. 97-106, 8th ACM International Conference on Web Search and Data Mining, WSDM 2015, Shanghai, China, 1/31/15. https://doi.org/10.1145/2684822.2685316

Rajadesingan A, Zafarani R, Liu H. Sarcasm detection on twitter:A behavioral modeling approach. In WSDM 2015 - Proceedings of the 8th ACM International Conference on Web Search and Data Mining. Association for Computing Machinery. 2015. p. 97-106. (WSDM 2015 - Proceedings of the 8th ACM International Conference on Web Search and Data Mining). doi: 10.1145/2684822.2685316

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abstract = "Sarcasm is a nuanced form of language in which individuals state the opposite of what is implied. With this intentional ambiguity, sarcasm detection has always been a challenging task, even for humans. Current approaches to automatic sarcasm detection rely primarily on lexical and linguistic cues. This paper aims to address the di-cult task of sarcasm detection on Twitter by leveraging behavioral traits intrinsic to users expressing sarcasm. We identify such traits using the user's past tweets. We employ theories from behavioral and psychological studies to construct a behavioral modeling framework tuned for detecting sarcasm. We evaluate our framework and demonstrate its efficiency in identifying sarcastic tweets.",

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Sarcasm detection on twitter:A behavioral modeling approach

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