Algerian dialect sentiment analysis in social networks

Abstract

This dissertation aims to explore the field of sentiment analysis as a key application of Natural Language Processing (NLP), with a special emphasis on the Arabic language and the Algerian dialect due to their linguistic diversity and the challenges they pose for automatic processing and comprehension. It covers the various stages of sentiment analysis, followed by preprocessing, feature extraction, and the development of classification models. The work also underscores the importance of NLP in understanding Arabic texts and examines the historical and cultural factors that have shaped the emergence and development of the Algerian dialect. From a practical standpoint, the study presents a sentiment analysis model and compares its results and performance with several other models to assess its effectiveness and accuracy in classifying sentiments within texts written in the Algerian dialect.