Fake Review Detection in Yelp Restaurant Reviews via Natural Language Processing

Fake reviews are becoming a greater problem for online platforms, especially in the restaurant world. These dodgy reviews can hurt businesses; smaller ones often pinch the most because they mess with people’s trust and sway their buying decisions. Traditional ways of sniffing out fake reviews, such as manually going through them, are relatively slow and not very reliable; however, they are effective only approximately 57% of the time. However, that is where machine learning comes in with natural language processing. It is a game changer that uses enormous datasets and smart algorithms to find those tells that give away fake reviews via sentiment analysis. By looking at how people write, things such as grammar and meaning, and how they behave, such as how engaged they are or when they post, machine learning can do way better than the previous methods can. This study is all about pushing for better fake review detection systems that can help both businesses and customers, hitting accuracy rates of over 95% via behavioral feature extraction.