Sarcasm Detection Algorithms

YAVANOĞLU U., Ibisoglu T. Y., Wicana S. G.

INTERNATIONAL JOURNAL OF SEMANTIC COMPUTING, vol.12, no.3, pp.457-478, 2018 (ESCI) identifier identifier

  • Publication Type: Article / Review
  • Volume: 12 Issue: 3
  • Publication Date: 2018
  • Doi Number: 10.1142/s1793351x18300017
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus
  • Page Numbers: pp.457-478
  • Keywords: Sarcasm, semantic analysis, machine learning, sarcasm detection, review, opinion mining, natural language processing, IRONY
  • Gazi University Affiliated: Yes


In this paper, we want to review one of the challenging problems for the opinion mining task, which is sarcasm detection. To be able to do that, many researchers tried to explore such properties in sarcasm like theories of sarcasm, syntactical properties, psycholinguistic of sarcasm, lexical feature, semantic properties, etc. Studies conducted within last 15 years have not only made progress in semantic features but have also shown increasing amounts of methods of analysis using a machine-learning approach to process data. Therefore, this paper will try to explain the most currently used methods to detect sarcasm. Lastly, we will present a result of our finding, which might help other researchers to gain a better result in the future.