You Are Your Check-In

Abstract

Currently the use of location-based social networks are becoming quite popular. For example, Foursquare reported 50 million users in 2014. Data from this type of system can be viewed as a source of sensing, in which the sensors are users with their mobile devices sharing data on various aspects of the city. This source of data enables large-scale study of urban social behavior and city dynamics. In this paper we show how we can use the signals emitted by Foursquare users to better understand the differences between the behavior of tourists and residents. We analyze tourists and residents in four popular cities around the world: London, New York, Rio de Janeiro and Tokyo. One of the contributions of this work is the spatio-temporal study of properties of the behavior of these two classes of users (tourists and residents). We have identified, for example, that some locations have features that are more correlated with the tourists' behavior, and also that even in places frequented by tourists as well as residents there are clear differences in the patterns of behavior of these classes. Our results could be useful in several cases, for example, to help in the development of new recommendation systems specific for tourists.

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