Reyes Pérez, A.; Rosso, P.; Buscaldi, D. (2012)  The research described in this paper focuses on analyzing two playful domains of language: humor and irony, in order to identify key values components for their automatic processing. In particular, we focus on describing a model for recognizing these phenomena in social media, such as "tweets". Our experiments are centered on five data sets retrieved from Twitter taking advantage of usergenerated tags, such as "#humor" and "#irony". The model, which is based on textual features, is assessed on two dimensions: representativeness and relevance. The results, apart from providing some valuable insights into the creative and figurative usages of language, are positive regarding humor, and encouraging regarding irony.
REF focus on humor and irony processing.
From humor recognition to irony detection: The figurative language of social media
Data Knowl. Eng.
Data Knowl. Eng.
Computer Science