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Exploring the realization of irony in Twitter data

Cynthia Van Hee (UGent) , Els Lefever (UGent) and Veronique Hoste (UGent)
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Abstract
Handling figurative language like irony is currently a challenging task in natural language processing. Since irony is commonly used in user-generated content, its presence can significantly undermine accurate analysis of opinions and sentiment in such texts. Understanding irony is therefore important if we want to push the state-of-the-art in tasks such as sentiment analysis. In this research, we present the construction of a Twitter dataset for two languages, being English and Dutch, and the development of new guidelines for the annotation of verbal irony in social media texts. Furthermore, we present some statistics on the annotated corpora, from which we can conclude that the detection of contrasting evaluations might be a good indicator for recognizing irony.
Keywords
verbal irony, figurative language processing, social media

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Citation

Please use this url to cite or link to this publication:

MLA
Van Hee, Cynthia, et al. “Exploring the Realization of Irony in Twitter Data.” LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, ELRA, 2016, pp. 1795–99.
APA
Van Hee, C., Lefever, E., & Hoste, V. (2016). Exploring the realization of irony in Twitter data. In LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION (pp. 1795–1799). Portoroz, SLOVENIA: ELRA.
Chicago author-date
Van Hee, Cynthia, Els Lefever, and Veronique Hoste. 2016. “Exploring the Realization of Irony in Twitter Data.” In LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 1795–99. ELRA.
Chicago author-date (all authors)
Van Hee, Cynthia, Els Lefever, and Veronique Hoste. 2016. “Exploring the Realization of Irony in Twitter Data.” In LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 1795–1799. ELRA.
Vancouver
1.
Van Hee C, Lefever E, Hoste V. Exploring the realization of irony in Twitter data. In: LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION. ELRA; 2016. p. 1795–9.
IEEE
[1]
C. Van Hee, E. Lefever, and V. Hoste, “Exploring the realization of irony in Twitter data,” in LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, Portoroz, SLOVENIA, 2016, pp. 1795–1799.
@inproceedings{7197428,
  abstract     = {{Handling figurative language like irony is currently a challenging task in natural language processing. Since irony is commonly used in user-generated content, its presence can significantly undermine accurate analysis of opinions and sentiment in such texts. Understanding irony is therefore important if we want to push the state-of-the-art in tasks such as sentiment analysis. In this research, we present the construction of a Twitter dataset for two languages, being English and Dutch, and the development of new guidelines for the annotation of verbal irony in social media texts. Furthermore, we present some statistics on the annotated corpora, from which we can conclude that the detection of contrasting evaluations might be a good indicator for recognizing irony.}},
  author       = {{Van Hee, Cynthia and Lefever, Els and Hoste, Veronique}},
  booktitle    = {{LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION}},
  isbn         = {{9782951740891}},
  keywords     = {{verbal irony,figurative language processing,social media}},
  language     = {{eng}},
  location     = {{Portoroz, SLOVENIA}},
  pages        = {{1795--1799}},
  publisher    = {{ELRA}},
  title        = {{Exploring the realization of irony in Twitter data}},
  year         = {{2016}},
}

Web of Science
Times cited: