A multidimensional approach for detecting irony in Twitter

作者：Reyes Antonio^*; Rosso Paolo; Veale Tony

来源：Language Resources and Evaluation, 2013, 47(1): 239-268.

DOI：10.1007/s10579-012-9196-x

• Irony detection
• Figurative language processing
• Negation
• Web text analysis

Irony is a pervasive aspect of many online texts, one made all the more difficult by the absence of face-to-face contact and vocal intonation. As our media increasingly become more social, the problem of irony detection will become even more pressing. We describe here a set of textual features for recognizing irony at a linguistic level, especially in short texts created via social media such as Twitter postings or %26quot;tweets%26quot;. Our experiments concern four freely available data sets that were retrieved from Twitter using content words (e.g. %26quot;Toyota%26quot;) and user-generated tags (e.g. %26quot;#irony%26quot;). We construct a new model of irony detection that is assessed along two dimensions: representativeness and relevance. Initial results are largely positive, and provide valuable insights into the figurative issues facing tasks such as sentiment analysis, assessment of online reputations, or decision making.

• 出版日期2013-3