Emotion Detection in Arabic Text using Machine Learning Methods
Abstract—Emotions are essential to any or all languages and are notoriously challenging to grasp. While numerous studies discussing the recognition of emotion in English, Arabic emotion recognition research remains in its early stages. The textual data with embedded emotions has increased considerably with the Internet and social networking platforms. This study aims to tackle the challenging problem of emotion detection in Arabic text. Recent studies found that dialect diversity and morpho- logical complexity in the Arabic language, with the limited access of annotated training datasets for Arabic emotions, pose the foremost significant challenges to Arabic emotion detection. Social media is becoming a more popular kind of communication where users can share their thoughts and express emotions like joy, sadness, anger, surprise, hate, fear, so on some range of subjects in ways they’d not typically neutralize person. Social media also present different challenges which include spelling mistakes, new slang, and incorrect use of grammar. The previous few years have seen a giant increase in interest in text emotion detection.
