A Review on Sarcasm Detection from Machine-Learning Perspective


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

11th IEEE International Conference on Semantic Computing (ICSC), California, Amerika Birleşik Devletleri, 30 Ocak - 01 Şubat 2017, ss.469-476 identifier identifier

  • Cilt numarası:
  • Doi Numarası: 10.1109/icsc.2017.74
  • Basıldığı Şehir: California
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Sayfa Sayıları: ss.469-476

Özet

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 done in the last 15 years not only made progress in semantic features, but also show increasing amount of method of analysis using a machine-learning approach to process data. Because of this reason, this paper will try to explain current mostly used method 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.