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Irony Detection for Dutch: a Venture into the Implicit

Aaron Maladry (UGent) , Els Lefever (UGent) , Cynthia Van Hee (UGent) and Veronique Hoste (UGent)
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Abstract
This paper presents the results of a replication experiment for automatic irony detection in Dutch social media text, investigating both a feature-based SVM classifier, as was done by Van Hee et al. (2017) and a transformer-based approach. In addition to building a baseline model, an important goal of this research is to explore the implementation of common-sense knowledge in the form of implicit sentiment, as we strongly believe that common-sense and connotative knowledge are essential to the identification of irony and implicit meaning in tweets. We show promising results and how the presented approach can provide a solid baseline and serve as a staging ground to build on in future experiments for irony detection in Dutch.
Keywords
LT3

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MLA
Maladry, Aaron, et al. “Irony Detection for Dutch: A Venture into the Implicit.” Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, Association for Computational Linguistics, 2022, pp. 172–81.
APA
Maladry, A., Lefever, E., Van Hee, C., & Hoste, V. (2022). Irony Detection for Dutch: a Venture into the Implicit. Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, 172–181. Dublin, Ireland: Association for Computational Linguistics.
Chicago author-date
Maladry, Aaron, Els Lefever, Cynthia Van Hee, and Veronique Hoste. 2022. “Irony Detection for Dutch: A Venture into the Implicit.” In Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, 172–81. Dublin, Ireland: Association for Computational Linguistics.
Chicago author-date (all authors)
Maladry, Aaron, Els Lefever, Cynthia Van Hee, and Veronique Hoste. 2022. “Irony Detection for Dutch: A Venture into the Implicit.” In Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, 172–181. Dublin, Ireland: Association for Computational Linguistics.
Vancouver
1.
Maladry A, Lefever E, Van Hee C, Hoste V. Irony Detection for Dutch: a Venture into the Implicit. In: Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis. Dublin, Ireland: Association for Computational Linguistics; 2022. p. 172–81.
IEEE
[1]
A. Maladry, E. Lefever, C. Van Hee, and V. Hoste, “Irony Detection for Dutch: a Venture into the Implicit,” in Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, Dublin, Ireland, 2022, pp. 172–181.
@inproceedings{8753092,
  abstract     = {{This paper presents the results of a replication experiment for automatic irony detection in Dutch social media text, investigating both a feature-based SVM classifier, as was done by Van Hee et al. (2017) and a transformer-based approach. In addition to building a baseline model, an important goal of this research is to explore the implementation of common-sense knowledge in the form of implicit sentiment, as we strongly believe that common-sense and connotative knowledge are essential to the identification of irony and implicit meaning in tweets. We show promising results and how the presented approach can provide a solid baseline and serve as a staging ground to build on in future experiments for irony detection in Dutch.}},
  author       = {{Maladry, Aaron and Lefever, Els and Van Hee, Cynthia and Hoste, Veronique}},
  booktitle    = {{Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis}},
  isbn         = {{978-1-955917-52-0}},
  keywords     = {{LT3}},
  language     = {{eng}},
  location     = {{Dublin, Ireland}},
  pages        = {{172--181}},
  publisher    = {{Association for Computational Linguistics}},
  title        = {{Irony Detection for Dutch: a Venture into the Implicit}},
  year         = {{2022}},
}