Analysis and Detection of Deceptive Product Reviews for E-Commerce Platforms Using Machine learning and Text Mining: A Systematic Literature Review

The use of online service platforms and the World Wide Web has gained immense popularity, especially during the Covid-19 outbreak, which led to lockdowns and social isolation. This surge in online activity has resulted in a massive increase in the products and services offered through these platforms, generating a substantial amount of user-generated information in the form of reviews. These reviews are valuable for both consumers and businesses, aiding in decision-making and improvements . However, the issue of fraudulent reviews has emerged, with some businesses hiring writers to post fake positive reviews about their own products or negative reviews about competitors. This misinformation necessitates a system to identify and eliminate misleading reviews . In this paper, a Machine Learning-based fake review detection model is proposed to determine the most effective classification algorithm for this purpose .