Paper: Modelling Irony in Twitter

ACL ID E14-3007
Title Modelling Irony in Twitter
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

Computational creativity is one of the central research topics of Artificial Intel- ligence and Natural Language Process- ing today. Irony, a creative use of language, has received very little atten- tion from the computational linguistics research point of view. In this study we investigate the automatic detection of irony casting it as a classification prob- lem. We propose a model capable of de- tecting irony in the social network Twit- ter. In cross-domain classification experi- ments our model based on lexical features outperforms a word-based baseline previ- ously used in opinion mining and achieves state-of-the-art performance. Our features are simple to implement making the ap- proach easily replicable.