Effect of Information Propagation on Business Popularity: A Case Study on Yelp

The penetration of smartphones and advancement of the location-based services have jointly contributed to the popularity of location-based social networking platforms such as Foursquare and Yelp. Business owners are important stakeholders of such location-based social network (LBSN) platforms, for whom setting up new businesses at the right location has immense importance in making a business popular. Given a wide variety of businesses, a single metric may not correctly capture the business popularity, rather, popularity measure should be specific to geographical regions, business category etc. In this paper, we systematically define popularity metrics and use them to label diverse businesses available in Yelp dataset. Notably, information diffusion plays a major role in popularizing businesses, word of mouth communication across customers facilitates information spread. This paper concentrates on two key modalities that exhibit a strong signature of business popularity: social connections across customers, showing high correlation with corresponding business popularity, and geographical proximity, which reveals two types of customers, namely, local visitor and foreign visitor observed through a comprehensive study on Yelp dataset. Depending on the business type and category, either local or foreign visitors play important role in making a business popular. Finally, we leverage on these signatures to predict business popularity and develop a recommendation model suggesting top regions to business owners for starting popular businesses. We show that both the models outperform the state-of-the-art baseline algorithms.