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Using E-Reputation for Sentiment Analysis: Twitter as a Case Study
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Author(s): Dhai Eddine Salhi (LIMOSE Laboratory, University of Mhamed Bougara, Boumerdes, Algeria), Abelkamel Tari (LIMED Laboratory, University Abderrahmane Mira, Bejaia, Algeria)and Mohand Tahar Kechadi (Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland)
Copyright: 2022
Pages: 17
Source title:
Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-6303-1.ch071
PurchaseView on the publisher's website for pricing and purchasing information.
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Abstract
In a competitive world, companies are looking to gain a positive reputation through these clients. Electronic reputation is part of this reputation mainly in social networks, where everyone is free to express their opinion. Sentiment analysis of the data collected in these networks is very necessary to identify and know the reputation of a companies. This paper focused on one type of data, Twits on Twitter, where the authors analyzed them for the company Djezzy (mobile operator in Algeria), to know their satisfaction. The study is divided into two parts: The first part was the pre-processing phase, where this research filtered the Twits (eliminate useless words, use the tokenization) to keep the necessary information for a better accuracy. The second part was the application of machine learning algorithms (SVM and logistic regression) for a supervised classification since the results are binary. The strong point of this study was the possibility to run the chosen algorithms on a cloud in order to save execution time; the solution also supports the three languages: Arabic, English, and French.
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