Predicting the star rating of a business on Yelp using graph convolutional neural networks

Ana-Maria Istrate

Abstract: Social media platforms have been rising steadily in recent years, influencing consumer spaces as a whole and individual users alike. Users also have the power of influencing the popularity of businesses or products on these platforms, driving the success level of different entities. Hence, understanding users' behavior is useful for businesses that want to cater to users' needs and know what market segment to direct efforts towards. In this paper, we are looking at how the star rating of a business on Yelp is determined by the profile of users who have rated it with a high score on Yelp. We are defining a graph between users on Yelp and businesses they gave high ratings to, and using graph convolutional neural networks to find node embeddings for businesses, by aggregating information from the users they are connected to. We show how a business's star rating can be predicted by aggregating local information about a business's neighborhood in the Yelp graph, as well as information about the business itself.