Automatic Detection of Irony: Opinion Mining in Microblogs and Social Media

By Farah Benamara, Jihen Karoui, Veronique Moriceau, et al.

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).

• Format: Hardcover
• Language: English
• ISBN: 178630399X
• ISBN13: 9781786303998
• Release Date: November 2019
• Publisher: Wiley-Iste
• Length: 210 Pages
• Weight: 1.14 lbs.
• Dimensions: 0.7" x 6.4" x 9.3"