Point of interest communities discovery over mobility data

Abstract

We analyze urban mobility and public places under a new perspective: how can we feature the places in a city based on how people move among them? To answer this question we need to combine places, like points of interest, with mobility information like the trajectories of individuals moving within a city. To accomplish this, we propose a methodology based on complex network analysis: we build a network of points of interests by connecting places by the individual trajectories passing through them. From such network we compute communities finding groups places highly connected by the mobility of the individuals. We present a case study on real trajectory dataset on the city of Milan, showing a complementary view on the urban mobility that is not covered by the state-of-the art techniques on mobility analysis.