Fake Review Detection Techniques on Online Products: An Empirical Study - Choukse, Satya Prakash; Meena, Pooja; Agrawal, Chetan (International Journal of Computer Sciences and Engineering, 2024)
E-commerce websites are becoming an essential component of daily living. The epidemic has quickly moved into the digital era and changed people`s online buying habits. Many individuals research items before making an online purchase by reading product reviews. Thus, reviews are crucial to a customer`s decision to purchase any goods. As a result, social media platforms and e-commerce sites like Flipkart, Amazon, and others get more bogus reviews. Robust and dependable approaches are required to identify phony reviews, which may be advantageous to both the seller and the client. Phony reviews have the power to promote poor items and disparage good ones. The goal of this survey article is to provide a broad overview of the many strategies used to these sorts of problems. This paper provides a thorough examination of several techniques to spam detection in machine learning (ML), natural language processing (NLP), sentiment analysis, and deep learning (DL).