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A multidimensional approach for detecting irony in Twitter.

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 r...

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Published in:Language Resources & Evaluation Vol. 47; no. 1; pp. 239 - 269
Main Authors: Reyes, Antonio, Rosso, Paolo, Veale, Tony
Format: Article
Published: Springer Nature Mar2013
Subjects:
Internet
Face-to-face communication
Intonation (Phonetics)
Linguistics
Social media
Twitter (Web resource)
Online Access:View this record in EBSCOhost
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          Reyes, Antonio
          Rosso, Paolo
          Veale, Tony
        affil:
          Natural Language Engineering Lab, ELiRF, Universidad Politécnica de Valencia, Valencia Spain
          School of Computer Science and Informatics, University College Dublin, Dublin Ireland
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        Internet
        Face-to-face communication
        Intonation (Phonetics)
        Linguistics
        Social media
        Twitter (Web resource)
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          Internet
          Face-to-face communication
          Intonation (Phonetics)
          Linguistics
          Social media
          Twitter (Web resource)
      keyword:
        Figurative language processing
        Irony detection
        Negation
        Web text analysis
      ab: 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 'tweets'. Our experiments concern four freely available data sets that were retrieved from Twitter using content words (e.g. 'Toyota') and user-generated tags (e.g. '#irony'). 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.
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      doctype: Article
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    language: English
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