Chinese Irony Corpus Construction and Ironic Structure Analysis

Non-literal expression recognition is a challenging task in natural language processing. An ironic expression implies the opposite of the literal meaning, causing problems in opinion mining and sentiment analysis. In this paper, ironic messages are collected from microblogs to form an irony corpus based on the use of emoticons, linguistic forms, and sentiment polarity. Five linguistic patterns are mined by using the proposed bootstrapping approach. We also analyze the linguistic structure and elements used to convey irony. Based on our observations, ironic words/phrases and contextual information are the necessary elements in irony, while the contextual information can be hidden in linguistic forms. A rhetorical element, which is optional in irony, can also be used to help strengthen the effects and understandability of an ironic expression. The ironic elements in each instance of our irony corpus are labelled based on this structure. This corpus can be used to study the usage of ironic expressions and the identification of ironic elements, and thus improve the performance of irony recognition.

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