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Please use this identifier to cite or link to this item: https://repository.esi-sba.dz/jspui/handle/123456789/257
Title: Analyse des sentiments Appliquée aux dialectes arabes
Authors: ALAHOUM, NAdjia
KOUADRI, AIchouch RAnia
Keywords: Sentiment Analysis
Opinion Mining
NLP
Arabic Dialect
Deep Learning
Machine Learning
Classification Models
Issue Date: 2021
Abstract: Sentiment analysis, also known as Opinion Mining, is a subfield of natural language processing. Since humans are omnipresent in today’s ultra-connected world thanks to social networks, they are constantly expressing their opinions on multiple topics in a multitude of occasions. Sentiment analysis is therefore crucial to identify the user’s opinion and interests. When the user is native of the Arabic world, things are not different, on the contrary, the richness and diversity of Arabic dialects makes social networks full of opinions. It is therefore wise to try to exploit this mass of information to extract useful information. In this work, we focus on the sentiment analysis of Arabic dialects (focal point on the Algerian dialect), in order to make a state of the art inventory of the different approaches and techniques used
Description: Pr. Sidi Mohamed BENSLIMANE Encadreur Dr. Badia KLOUCHE Co-Encadreur
URI: https://repository.esi-sba.dz/jspui/handle/123456789/257
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