Clues for detecting irony in user-generated contents: oh...!! it's "so easy" ;-)
Proceedings of the 1st international CIKM workshop on Topic-sentiment analysis for mass opinion
Identifying sarcasm in Twitter: a closer look
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
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Speakers and listeners make use of a variety of pragmatic factors to produce and identify sarcastic statements. It is also possible that lexical factors play a role, although this possibility has not been investigated previously. College students were asked to read excerpts from published works that originally contained the phrase said sarcastically, although the word sarcastically was deleted. The participants rated the characters' statements in these excerpts as more likely to be sarcastic than those from similar excerpts that did not originally contain the word sarcastically. The use of interjections, such as gee or gosh, predicted a significant amount of the variance in the participants' ratings of sarcastic intent. This outcome suggests that sarcastic statements may be more formulaic than previously realized. It also suggests that computer software could be written to recognize such lexical factors, greatly increasing the likelihood that non-literal intent could be correctly interpreted by such programs, even if they are unable to identify the pragmatic components of nonliteral language.