Modelling Irony in Twitter
Francesco Barbieri, Horacio Saggion · 2014
Computational creativity is one of the central research topics of Artificial Intelligence and Natural Language Processing today.Irony, a creative use of language, has received very little attention from the computational linguistics research point of view.In this study we investigate the automatic detection of irony casting it as a classification problem.We propose a model capable of detecting irony in the social network Twitter.In cross-domain classification experiments our model based on lexical features outperforms a word-based baseline previously used in opinion mining and achieves state-of-the-art performance.Our features are simple to implement making the approach easily replicable.