Exploiting emojis for sarcasm detection

Jayashree Subramanian, Varun Sridharan, Kai Shu, Huan Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Modern social media platforms largely rely on text. However, the written text lacks the emotional cues of spoken and face-to-face dialogue, ambiguities are common, which is exacerbated in the short, informal nature of many social media posts. Sarcasm represents the nuanced form of language that individuals state the opposite of what is implied. Sarcasm detection on social media is important for users to understand the underlying messages. The majority of existing sarcasm detection algorithms focus on text information; while emotion information expressed such as emojis are ignored. In real scenarios, emojis are widely used as emotion signals, which have great potentials to advance sarcasm detection. Therefore, in this paper, we study the novel problem of exploiting emojis for sarcasm detection on social media. We propose a new framework ESD, which simultaneously captures various signals from text and emojis for sarcasm detection. Experimental results on real-world datasets demonstrate the effectiveness of the proposed framework.

Original languageEnglish (US)
Title of host publicationSocial, Cultural, and Behavioral Modeling - 12th International Conference, SBP-BRiMS 2019, Proceedings
EditorsRobert Thomson, Christopher Dancy, Ayaz Hyder, Halil Bisgin
PublisherSpringer Verlag
Pages70-80
Number of pages11
ISBN (Print)9783030217402
DOIs
StatePublished - Jan 1 2019
Event12th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2019 - Washington D.C., United States
Duration: Jul 9 2019Jul 12 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11549 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2019
CountryUnited States
CityWashington D.C.
Period7/9/197/12/19

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Subramanian, J., Sridharan, V., Shu, K., & Liu, H. (2019). Exploiting emojis for sarcasm detection. In R. Thomson, C. Dancy, A. Hyder, & H. Bisgin (Eds.), Social, Cultural, and Behavioral Modeling - 12th International Conference, SBP-BRiMS 2019, Proceedings (pp. 70-80). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11549 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-21741-9_8