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- W4386005103 abstract "This paper aims to develop a fake product review recognition system on Amazon using Python code. e-Commerce websites form an ever-expanding portion of the global business market, and reviews play a vital role in deciding the authenticity and quality of a product. Reviews and comments play a vital role in the e-commerce domain contributing to a product’s and in turn a seller’s good or bad reputation. There are often fake reviews posted on these platforms which ultimately result in either raising or dropping the ratings of these products. To promote products and disparage rivals, immoral actors hire bot farms, purchase legitimate accounts, and use Sybil accounts. Many businesses employ people to post fictitious favourable reviews about their goods or services or unfairly critical reviews about the goods or services of their rivals. This procedure provides inaccurate information to potential buyers of these goods; hence we need a way to identify and eliminate bogus reviews. Moreover. It directly affects the reliability of both the seller as well as the platform. Through this project, we aim to utilize SVM techniques in Python script to differentiate fake reviews from authentic ones, which ultimately decide the quality of the product and reliability of the seller." @default.
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- W4386005103 date "2023-01-01" @default.
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- W4386005103 title "Fake Review Recognition Using an SVM Model" @default.
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- W4386005103 doi "https://doi.org/10.1007/978-3-031-37963-5_61" @default.
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