Irony Detection for Dutch: a Venture into the Implicit

Publication type
U
Publication status
Published
Authors
Maladry, A, Lefever, E., Van Hee, C., & Hoste, V.
Series
Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis
Pagination
172-181
Publisher
Association for Computational Linguistics (Dublin, Ireland)
Conference
12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, collocated with ACL 2022 (Dublin, Ireland)
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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.