Sentiment Analysis of Algerian Dialect Using a Deep Learning Approach
No Thumbnail Available
Date
2022-01-24
Journal Title
Journal ISSN
Volume Title
Publisher
University of Eloued جامعة الوادي
Abstract
Nowadays 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.
Description
Forum Intervention of Artificial Intelligence and Its Applications. Faculty of Exat science. University of Eloued
Keywords
entiment Analysis · Deep Learning · CNN · Algerian Dialect · NLP
Citation
Klouche, 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]