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Overview of the Task on Irony Detection in Spanish Variants

This paper introduces IroSvA, the first shared task fully dedicated to identify the presence of irony in short messages (tweets and news comments) written in three different variants of Spanish. The task consists in: given a message, automatic systems should recognize whether the message is ironic or not. Moreover, with respect to the previous tasks on irony detection, the messages are not considered as isolated texts but together with a given context (e.g. a headline or a topic). The task is comprised by three different subtasks: i) irony detection in tweets from Spain, ii) irony detection in Mexican tweets, and iii) irony detection in news comments from Cuba. These subtasks aim at studying the way irony changes across the distinct Spanish variants. We received 14 submissions from 12 teams. Participating systems were evaluated against the test dataset using F1 macro averaged. The highest classification scores obtained for the three subtasks are F1=0.7167, F1=0.6803, and F1=0.6596, respectively.