Arabic Sentiment Analysis

Arabic sentiment analysis (ASA) focuses on automatically determining the emotional tone expressed in Arabic text, a challenging task due to the language's rich morphology and the diversity of its dialects. Current research emphasizes the development and application of deep learning models, particularly transformer architectures like BERT and its Arabic variants, along with convolutional and recurrent neural networks, to improve accuracy and address issues like homograph ambiguity and class imbalance. The field's advancements are crucial for various applications, including social media monitoring, market research, and the development of more effective human-computer interaction systems in Arabic-speaking communities. A significant ongoing challenge is the need for larger, more diverse datasets, especially those encompassing Arabic dialects beyond Modern Standard Arabic.