Ironic Gestures and Tones in Twitter
Authors: Simona Frenda (Università di Torino, GruppoMeta, 2017)
Topic: Sentiment, Emotion, Irony, Hate

Abstract
Automatic irony detection is a young field of research related to Sentiment Analysis. When dealing with social media data, the shortness of text and the extraction of the statement from his context usually makes it hard to understand irony even for humans but especially for machines. In this paper we propose an analysis of the role that textual information plays in the perception and construction of irony in short texts like tweets. We will focus on the impact of conventional expedients of digital writing, which seem to represent a substitution of typical gestures and tones of oral communication, in figurative interpretation of messages in Italian language. Elaborated computational model has been exploited in the development of an irony detection system, which has been evaluated in the Sentipolc's shared task at EVALITA 2016.

Introduction
The growing scientific interest on natural language understanding has been supported in the last decade by a great amount of user-generated texts available on the Web. People usually use social media platforms, such as Facebook and Twitter, to express their opinions on different topics, which can be exploited, for example, by companies for marketing researches. This is one of the motivations which prompted actual research in this direction on automatic analysis of short-texts. Social micro-texts are great examples of rhetorical production due to their shortness, which supports the creativity of linguistic expressions AUTHOR. In fact 140 characters of tweets encourage users to use some creative devices in order to communicate briefly their opinions or their feelings about events, products, services or other individuals. Among creative devices, irony and sarcasm hinder correct sentiment analysis of texts and, therefore, correct opinion mining. Indeed, irony is a figurative language device used to convey the opposite of literal meaning: contrarium quod dicitur intelligendum est (Quintiliano, Institutio Oratoria, 9, 22-44). In order to express an ironic utterance in short text, users prefer to use conventional expedients in digital writing or particular linguistic constructs which seem to represent a substitution of typical gestures and tones of oral communication. These reveal themselves as good clues for Irony Detection as demonstrated by results obtained with our system participating in SENTIPOLC's at EVALITA 2016 AUTHOR, where we ranked third on twelve participants. In this paper we present linguistic analysis on ironic tweets extracted from corpora used in SENTIPOLC and computational model elaborated in Master's thesis upon which our rule-based system is based.

Conclusion
Although limited amount of Italian ironic examples, this analysis and the results of developed computational system AUTHOR show that people tend to use textual and conventional expedients of oral communication to express irony in informal context as social networks. We can observe this in Figure 1 and 2, where some linguistic constructions expressing tone and accent of user-speaker, like regional expressions and heavy punctuation, are used mainly in ironic tweets. With respect to ironic hashtags we can observe that same hashtags are mentioned in different ironic tweets in both corpora, revealing their important role of established conventional elements in communication in social networks. Finally, in Figure 3 and 4 we can observe that there are cases of incongruity between literal and real meaning, for example there are sentences with negative polarity that contain positive interjections or exclamatory constructions used, indeed, in ironic manner. It is interesting to underline that most of ironic tweets are negative in both corpora: 493 negative ironic tweets on 564 ironic tweets in SENTIPOLC 2014 corpus and 742 on 865 in SENTIPOLC 2016 corpus. In this scenario where automatic irony detection is still challenging for Italian, pragmatic analysis of ironic texts allows to take a closer look at how people use the language and his expedients to express irony.