A comparison of Foursquare and Instagram to the study of city dynamics and urban social behavior

Abstract

Social media systems allow a user connected to the Internet to provide useful data about the context in which they are at any given moment, such as Instagram and Foursquare, which are called participatory sensing systems. Location sharing services are examples of participatory sensing systems. The sensed data is a check-in of a particular place that indicates, for instance, a restaurant in a specific location, and also a signal from a user expressing his/her preference. From a participatory sensing system we can derive a participatory sensor network. In this work we compare two different participatory sensor networks, one derived from Instagram, and another one derived from Foursquare. In Instagram, the sensed data is a picture of a specific place. On the other hand, in Foursquare the sensed data is the actual location associated with a specific category of place (e.g., restaurant). Using those social networks we can extract information in many ways. In this work we are interested in comparing two datasets of Foursquare and two datasets of Instagram. We analyze those datasets to investigate whether we can observe the same users' movement pattern, the popularity of regions in cities, the activities of users who use those social networks, and how users share their content along the time. In answering those questions, we want to better understand location-related information, which is an important aspect of the urban phenomena.