Klouche, BadiaBenslimane, Sidi MohamedMahammed, Nadir2022-04-172022-04-172022-01-24Klouche, Badia • Benslimane, Sidi Mohamed• Mahammed, Nadir. Sentiment Analysis of Algerian Dialect Using a Deep Learning Approach,. Forum of Artificial Intelligence and Its Applications. 24-26 Jan 2022. Faculty of Exat science. University of Eloued. [visited in ../../….]. available from [copy the link here]https://dspace.univ-eloued.dz/handle/123456789/10844Forum Intervention of Artificial Intelligence and Its Applications. Faculty of Exat science. University of ElouedNowadays the Internet has become an essential tool for exchanging information, both on a personal and professional level. Today, the analysis of sentiment offers us a great interest for research, marketing and industry. With millions of comments and tweeting published every day, the information available on the Internet and in social media has become a gold mine for companies developing in their production, management and distribution. In this article, we propose a novel approach to analyze the sentiments of the Algerian dialect for the benefit of the Algerian Telephone Operator Ooredoo. The proposed approach is based on a deep learning model, which provides state-of-the-art results on a dataset written in Algerian dialect. In this study, the Facebook comments shared in Modern Standard Arabic (MSA) and Algerian dialect of the customers of the Algerian telephone operator Ooredoo are analyzed in order to allow the operator to retain and satisfy its customers to the maximum. Experimental results show that deep learning approaches outperformed traditional methods of sentiment.enentiment Analysis · Deep Learning · CNN · Algerian Dialect · NLPOther