Une approche d’Analyse des Sentiments Appliquée au Dialecte Algérien

Abstract

oday, sentiment analysis holds great importance in various fields such as politics, production, and services, among others. Currently, social media platforms are filled with texts in which internet users express their opinions on different subjects, and the value of their opinions is considerable. Understanding the content conveyed by these texts is essential. It can be said that a good manager is one who attentively listens to the opinions of citizens. In this regard, sentiment analysis is highly significant in meeting the needs of citizens. In this work, we will create an LSTM model that will analyze and classify a set of posts from social media. Subsequently, we will develop a web application for analyzing user opinions. The defined classes are positive and negative. This work stands out among the few that utilize models to analyze comments using the Algerian dialect. The obtained results are encouraging, with an accuracy of 84.7%, demonstrating the system’s ability to distinguish between negative and positive discourse.