Making Objective Decisions from Subjective Data: Detecting Irony in Customers Reviews

Autores UPV
Año
Revista DECISION SUPPORT SYSTEMS

Abstract

The research described in this paper is focused on analyzing two playful domains of language: humor and irony, in order to identify key values components for their automatic processing. In particular, we are focused 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 user-generated 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.