kamel Tools for Processing Arabic Texts on Social Media: An Analytical Study within the Framework of Big Data

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کلية الاداب جامعه المنيا مصر

Abstract

This research examines sentiment analysis using "Kamil" tools for Arabic text processing, focusing on how this analysis can help understand and address contemporary issues. It explores the use of artificial intelligence techniques for Arabic text analysis, highlighting challenges in Arabic language processing and the need for improved accuracy. The study includes real-life examples demonstrating how sentiment analysis can provide deeper insights into social, political, and economic issues, aiding in decision-making and strategy development.



The research aims to offer a deeper understanding of how texts express emotions related to these issues through "Kamil" tools, contributing to better comprehension of the impact of current events on public sentiment and the development of effective strategies for managing social and media-related challenges.



Based on the analysis, results show that issues related to social conflict, such as "Ahmed Elawady and Hossam Bouji" (81% positive) and "The Reconciliation Feast Between the Tribes" (67% positive), receive relatively positive responses. In contrast, personal issues like "The Story of Being Expelled from Home" (66% positive) and "The Daughter of the Ismailia Victim" (70% positive) receive less positive acceptance. "The Message from the Mansoura Teacher" received the highest percentage of negative comments (53%), reflecting notable negative reactions to individual issues.

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