Sentiment Analysis for Arabic Language using Advanced Deep Learning Techniques

Abstract

This master’s thesis focuses on the Sentiment Analysis for Arabic languages using Advanced Deep Learning Techniques. The aim of this study is to develop an intelligent system that can automatically predict the sentiment from Arabic text based on Natural language processing . Traditional manual analysis methods are time-consuming, costly, and prone to human errors. By leveraging advancements in deep learning, Natural Language processing, an AI-based system can provide accurate and real-time information about the sentiment status of humans , enabling businesses to take preventive decision and optimize their products and services quality. The proposed system combines deep learning techniques with Natural language processing to assist businesses in maintaining their gains and reducing losses. This thesis presents the design, implementation, and evaluation of the system, demonstrating its effectiveness in Sentiment Analysis for Arabic Language.