Exploring the Realization of Irony in Twitter Data

TitleExploring the Realization of Irony in Twitter Data
Publication TypeConference Paper
Year of Publication2016
AuthorsVan Hee, C, Lefever, E, Hoste, V
Conference NameTenth International Conference on Language Resources and Evaluation (LREC 2016)
PublisherEuropean Language Resources Association (ELRA)
Conference LocationPortorož, Slovenia
ISBN Number978-2-9517408-9-1
AbstractHandling 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.