Fake Review Detection on Yelp Dataset Using Classification Techniques in Machine Learning

Abstract

This paper provides a summary of our research, which aims to build a machine learning model that can detect whether the reviews on Yelp’s dataset are true or fake. In particular, we applied and compared different classification techniques in machine learning to find out which one would give the best result. Brief descriptions for each of the classification techniques are provided to aid understanding of why some methods are better than others in some cases. The best result was achieved by using the XGBoost classification technique, with F-1 score reaching 0.99 in prediction.