Emotion detection in Arabic text is an emerging research area, but the efforts in this new field are hindered by the very limited availability of Arabic datasets annotated with emotions. We then present an Arabic tweet dataset that we have built to serve this task. Preliminary experiments carried out on this dataset for emotion detection. The results of these experiments are provided as a benchmark for future studies and comparisons with other emotion detection models. The best results over a set of eight emotions were obtained using a complement Naïve Bayes algorithm with an overall accuracy of 68.12 %.
Amr Al-Khatib, Samhaa El-Beltagy. "Emotional Tone Detection in Arabic Tweets". In proceedings of the 18th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing 2017); Budapest, Hungary, 2017.