Sarcasm SIGN: Interpreting Sarcasm with Sentiment Based Monolingual Machine Translation
Lotem Peled, Roi Reichart · 2017
Sarcasm is a form of speech in which speakers say the opposite of what they truly mean in order to convey a strong sentiment.In other words, "Sarcasm is the giant chasm between what I say, and the person who doesn't get it.".In this paper we present the novel task of sarcasm interpretation, defined as the generation of a non-sarcastic utterance conveying the same message as the original sarcastic one.We introduce a novel dataset of 3000 sarcastic tweets, each interpreted by five human judges.Addressing the task as monolingual machine translation (MT), we experiment with MT algorithms and evaluation measures.We then present SIGN: an MT based sarcasm interpretation algorithm that targets sentiment words, a defining element of textual sarcasm.We show that while the scores of n-gram based automatic measures are similar for all interpretation models, SIGN's interpretations are scored higher by humans for adequacy and sentiment polarity.We conclude with a discussion on future research directions for our new task. 1