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In the age of digital commerce, web users now have access to a substantial amount of data on the web due to the quick development of web technology. Reviews and ratings are a rich source of information on a number of e-commerce sites, including Amazon, Flipkart, and Ajio. Amazon is among popular e-commerce websites to purchase online products, because it enables you to have a look on thousands of additional customer reviews for the products you are considering. These reviews contains helpful details regarding the product like its quality, along with recommendations. In the proposed work reviews have been categorized into three categories as neutral, positive, and negative using Machine learning from ecommerce website amazon. Out of various natural language processing techniques like text-preprocessing, Feature Engineering and model building have been used for data manipulation. Support Vector machine and naïve bayes machine learning algorithms are used to analyze customer feedback about items using sentiment classification.
Chauhan et al. (Fri,) studied this question.