SOUKHRIA: Towards an Irony Detection System for Arabic in Social Media

Jihen Karoui, Farah Banamara Zitoune, Véronique Moriceau · Procedia Computer Science · 2017

This paper presents a supervised learning method for irony detection in Arabic tweets. A binary classifier uses four groups of features whose efficiency has been empirically proved in other languages such as French, English, Italian, Dutch and Japanese. Our first results are encouraging and show that state of the art features can be successfully applied to Arabic language with an accuracy of 72.76%.

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