A Smarter Way to Filter Reviews and Identify Fake Reviews Using Random Forest for an Improved Online Shopping Experience
Kumar P, Senthil Pandi S, Bharath Kumar L, Karthick R · 2025
The e-commerce system is expanding at a quick pace since online products are the main emphasis of the retail industry's future. Improving the customer experience and the review system to provide additional online purchasing suggestions is our core goal. While product ratings and reviews are currently available, not all reviews are reliable, so some customers may be hesitant to make a purchase based only on them. Our proposed Fake Review Detection System is an Intelligent Interface that collects product-related reviews from Amazon, Flipkart, and Daraz, analyses them, and then returns the original rating to the customer. This would help eliminate these types of fake reviews and give users access to the real ratings and reviews of the products. Another way we bring users closer to our platform is by allowing them to connect with friends and family through the contacts list. This way, users can ask their friends and family for reviews in real-time through the chat feature. If the user has an account on the website, they can access their contact list in their Gmail account using the Google Contacts API. Afterwards, the user can inquire about the product's real-time evaluation via the chat box from someone who has really tried it. Additionally, we have public reviews where we have included fraudulent review detection using Random Forest, making the service even more trustworthy and reputable for customers who desire anonymity. As a result, we've improved our website to make online buying more reliable and secure, which should lead to more product sales.