This document proposes a system to detect fake product reviews on e-commerce sites. The system uses sentiment analysis, content similarity analysis, and review deviation analysis to identify fake reviews. It extracts product reviews from websites, preprocesses the data, and uses three techniques to detect fake reviews. The fake reviews are then used to train a classifier to label new reviews as fake or genuine. The system was able to detect 111 fake reviews out of 300 with the classifier identifying an additional 18 fake reviews. The techniques aim to make online shopping reviews more trustworthy.