Emotion Detection in Arabic Text in Social Media: A Brief Survey

Abstract

Emotion detection in Arabic text in social media has gained significant attention due to the increasing use of social media platforms in the Arab world. It is a special case of affective computing that relies on natural language processing techniques to recognize emotions from written text. This article provides a comprehensive review of different approaches used in developing models for emotion detection in Arab textual data in social media. Social media have a substantial impact on societies and have contributed significantly to many fields (marketing, recommendation systems, etc.). Arabic language texts on social networking sites in all their forms (posts - comments - messages - any other form) express the personal feelings of the person concerned; if they are understood correctly, the understanding of the written text will be correct. Scientific research has recently increased in this field to determine people's feelings through their writing of texts. In addition, we have highlighted the utilization of deep learning architectures in the improvement of the performances of models for different types of deep learning models.