Sentiment Analysis of Product Customer Reviews on Tunisian Online Sale Sites
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In this paper, the Customer Reviews Analysis of Products, collected from Tunisian online retail platforms, is performed by collecting the data with the help of the web scraping method. Approaches comprise a language detection process that will handle the reviews in any language, followed by sentiment analysis, which in turn forms the polarity of comments: positive, negative, or neutral. The classification of opinions has been done using some machine learning algorithms: Support Vector Machines, Decision Trees, Random Forests, and Naive Bayes. Besides, in this paper, the Tf-Idf method is applied to represent and classify the texts. This research will give some effective insights into improving customer satisfaction and optimizing business strategy regarding the context of Tunisian e-commerce.
