Measuring user activity on an online location-based social network

While in recent years online social networks have been largely shaping user experience on the Web, only in the last year there has been a soaring increase of novel location-based social applications. By allowing users to check-in at places and share their location with friends, these social platforms provide a new facet of user online behavior. In this work we present a measurement study of user activity on a popular online location-based social network with hundreds of thousands of users. We study not only how users connect with friends but also how they check-in at different places. We describe how, while the number of friends appears distributed according to a Double-Pareto law, both the number of check-ins and the number of places per user are better described by log-normal distributions. Moreover, we report how user activity spans decay faster than exponentially and how, over time, users add friends more quickly than they accumulate check-ins and places. Our findings suggest that the difference in the distribution of friends and check-ins/places may be motivated by physical constraints that do not allow users to steadily visit very large numbers of new places, while online friends can be added at virtually no cost. These results shed new light on how users engage with location-based online social networks and prompt many more research questions.