Sarcasm SIGN: Interpreting Sarcasm with Sentiment Based Monolingual Machine Translation

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, pages 1690–1700 Vancouver, Canada, July 30 - August 4, 2017. c⃝2017 Association for Computational Linguistics https://doi.org/10.18653/v1/P17-1155 Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, pages 1690–1700 Vancouver, Canada, July 30 - August 4, 2017. c⃝2017 Association for Computational Linguistics https://doi.org/10.18653/v1/P17-1155 Sarcasm SIGN: Interpreting Sarcasm with Sentiment Based Monolingual Machine Translation Lotem Peled and Roi Reichart Faculty of Industrial Engineering and Management, Technion, IIT splotem@campus.technion.ac.il, roiri@ie.technion.ac.il Abstract Sarcasm is a form of speech in which speakers say the opposite of what they truly mean in order to convey a strong sen- timent. In other words, ”Sarcasm is the giant chasm between what I say, and the person who doesn’t get it.”. In this pa- per 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 sar- castic tweets, each interpreted by five hu- man judges. Addressing the task as mono- lingual machine translation (MT), we ex- periment with MT algorithms and evalu- ation measures. We then present SIGN: an MT based sarcasm interpretation algo- rithm that targets sentiment words, a defin- ing element of textual sarcasm. We show that while the scores of n-gram based au- tomatic measures are similar for all inter- pretation 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 1 Introduction Sarcasm is a sophisticated form of communica- tion in which speakers convey their message in an indirect way. It is defined in the Merriam- Webster dictionary (Merriam-Webster, 1983) as the use of words that mean the opposite of what 1Our dataset, consisting of 3000 sarcastic tweets each augmented with five interpretations, is available in the project page: https://github.com/Lotemp/ SarcasmSIGN. The page also contains the sarcasm inter- pretation guidelines, the code of the SIGN algorithms and other materials related to this project. one would really want to say in order to insult someone, to show irritation, or to be funny. Con- sidering this definition, it is not surprising to find frequent use of sarcastic language in opinionated user generated content, in environments such as Twitter, Facebook, Reddit and many more. In textual communication, knowledge about the speaker’s intent is necessary in order to fully un- derstand and interpret sarcasm. Consider, for ex- ample, the sentence ”what a wonderful day”. A literal analysis of this sentence demonstrates a positive experience, due to the use of the word wonderful. However, if we knew that the sentence was meant sarcastically, wonderful would turn into a word of a strong negative sentiment. In spoken language, sarcastic utterances are often accompa- nied by a certain tone of voice which points out the intent of the speaker, whereas in textual com- munication, sarcasm is inherently ambiguous, and its identification and interpretation may be chal- lenging even for humans. …

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