ICWSM — A Great Catchy Name: Semi-Supervised Recognition of Sarcastic Sentences in Online Product Reviews

Authors

  • Oren Tsur The Hebrew University
  • Dmitry Davidov The Hebrew University
  • Ari Rappoport The Hebrew University

Keywords:

sentiment analysis, opinion mining, sarcasm recognition, review mining, amazon reviews, sarcasm

Abstract

Sarcasm is a sophisticated form of speech act widely used in online communities. Automatic recognition of sarcasm is, however, a novel task. Sarcasm recognition could contribute to the performance of review summarization and ranking systems. This paper presents SASI, a novel Semi-supervised Algorithm for Sarcasm Identification that recognizes sarcastic sentences in product reviews. SASI has two stages: semi-supervised pattern acquisition, and sarcasm classification. We experimented on a data set of about 66000 Amazon reviews for various books and products. Using a gold standard in which each sentence was tagged by 3 annotators, we obtained precision of 77% and recall of 83.1% for identifying sarcastic sentences. We found some strong features that characterize sarcastic utterances. However, a combination of more subtle pattern-based features proved more promising in identifying the various facets of sarcasm. We also speculate on the motivation for using sarcasm in online communities and social networks.

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Published

2010-05-16

How to Cite

Tsur, O., Davidov, D., & Rappoport, A. (2010). ICWSM — A Great Catchy Name: Semi-Supervised Recognition of Sarcastic Sentences in Online Product Reviews. Proceedings of the International AAAI Conference on Web and Social Media, 4(1), 162-169. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/14018