Exploring the realization of irony in Twitter data

Publication type
P1
Publication status
Published
Authors
Van Hee, C., Lefever, E., & Hoste, V.
Series
LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
Pagination
1795-1799
Publisher
ELRA
Conference
10th International Conference on Language Resources and Evaluation (LREC) (Portoroz, SLOVENIA)
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(.pdf)
Project
AMiCA
View in Biblio
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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.