Review on Fake Review Detection and Classific...

Review on Fake Review Detection and Classification using AI Techniques on Amazon Dataset

Author Name : Abhijeet Giri, Devendra Kumar Bajpai, P. K. Sharma

ABSTRACT The rapid expansion of e-commerce platforms has led to an influx of user-generated reviews that significantly influence consumer decisions. However, the presence of fake reviews—fabricated or biased reviews designed to manipulate product ratings—poses a major challenge to maintaining the integrity of online marketplaces. Detecting and classifying fake reviews has become an essential area of research to safeguard user trust and ensure fair market competition. This review paper explores the application of Artificial Intelligence (AI) techniques for detecting and classifying fake reviews on the Amazon dataset. Various machine learning and deep learning methods, such as Decision Trees, Support Vector Machines (SVM), Naive Bayes, and Neural Networks, have demonstrated their potential to effectively address this issue. The review discusses the advantages and limitations of these methods and highlights the role of natural language processing (NLP) for feature extraction and representation