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%.
Karoui, J., Zitoune, F. B., & Moriceau, V. (2017). SOUKHRIA: Towards an Irony Detection System for Arabic in Social Media. In Procedia Computer Science (Vol. 117, pp. 161–168). Elsevier B.V. https://doi.org/10.1016/j.procs.2017.10.105