Ooredoo Rayek

Author:

Klouche Badia1,Benslimane Sidi Mohamed2ORCID,Bennabi Sakina Rim3

Affiliation:

1. LabRI-SBA Laboratory, Ecole Superieure en Informatique, Sidi Bel Abbes, Algeria

2. LabRI-SBA Laboratory, Ecole Superieure en Informatique, Sidi Bel-Abbes, Algeria

3. Ecole Superieure en Informatique, Sidi Bel Abbes, Algeria

Abstract

Sentiment analysis is one of the recent areas of emerging research in the classification of sentiment polarity and text mining, particularly with the considerable number of opinions available on social media. The Algerian Operator Telephone Ooredoo, as other operators, deploys in its new strategy to conquer new customers, by exploiting their opinions through a sentiments analysis. The purpose of this work is to set up a system called “Ooredoo Rayek”, whose objective is to collect, transliterate, translate and classify the textual data expressed by the Ooredoo operator's customers. This article developed a set of rules allowing the transliteration from Algerian Arabizi to Algerian dialect. Furthermore, the authors used Naïve Bayes (NB) and (Support Vector Machine) SVM classifiers to assign polarity tags to Facebook comments from the official pages of Ooredoo written in multilingual and multi-dialect context. Experimental results show that the system obtains good performance with 83% of accuracy.

Publisher

IGI Global

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. AlgBERT: Automatic Construction of Annotated Corpus for Sentiment Analysis in Algerian Dialect;ACM Transactions on Asian and Low-Resource Language Information Processing;2023-12-19

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