Automatic Detection of Irony

Opinion Mining in Microblogs and Social Media

Automatic Detection of Irony

Jihen Karoui, AUSY, France
Farah Benamara, University in Toulouse, France
Véronique Moriceau, Paul Sabatier University, France

ISBN : 9781786303998

Publication Date : November 2019

Hardcover 210 pp

135.00 USD



In recent years, there has been a proliferation of opinion-heavy texts on the Web: opinions of Internet users, comments on social networks, etc. Automating the synthesis of opinions has become crucial to gaining an overview on a given topic. Current automatic systems perform well on classifying the subjective or objective character of a document. However, classifications obtained from polarity analysis remain inconclusive, due to the algorithms' inability to understand the subtleties of human language.

Automatic Detection of Irony presents, in three stages, a supervised learning approach to predicting whether a tweet is ironic or not. The book begins by analyzing some everyday examples of irony and presenting a reference corpus. It then develops an automatic irony detection model for French tweets that exploits semantic traits and extralinguistic context. Finally, it presents a study of portability in a multilingual framework (Italian, English, Arabic).


1. From Opinion Analysis to Figurative Language Treatment.
2. Toward Automatic Detection of Figurative Language.
3. A Multilevel Scheme for Irony Annotation in Social Network Content.
4. Three Models for Automatic Irony Detection.
5. Towards a Multilingual System for Automatic Irony Detection.

About the authors/editors

Jihen Karoui is Research and Development Project Manager at AUSY, France.

Farah Benamara is a Senior Lecturer at Paul Sabatier University in Toulouse, France.

Véronique Moriceau is a Senior Lecturer at Paul Sabatier University.

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