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User association analysis of locales on location based social networks

In recent years, location-based social networks (LBSNs) have received high attention. While this new breed of social networks is nascent, there is no large-scale analysis conducted to investigate the associations among users in locales of the network. In this paper, we propose four locale based metrics, including Locale Clustering Coefficient, Inward Locale Transitivity, Locale Assortativity Coefficient, and Locale Assortability Coefficient to make association analysis on EveryTrail, a popular LBSN specialized on sharing trips. Based on the analysis result, we observe that people who share more trajectories will get more attention by other users, and people who are popular will connect to the people who are also popular.