Fake Product Review Detection and Sentiment Analysis using Machine Learning

A fraudulent review is intentionally deceptive product feedback designed to mislead readers. A machine learning-based solution is presented to automatically identify and eliminate fraudulent reviews. The model incorporates Natural Language Processing (NLP) for feature extraction and employs hybrid methods for precise identification. The system delivers tailored and reliable review suggestions by integrating information filtering with user profiles derived via collaborative filtering. Experimental findings indicate that the suggested methodology attains superior accuracy compared to current recommendation systems.