A Tale of Many Cities: Universal Patterns in Human Urban Mobility

Anastasios Noulas,Salvatore Scellato,Massimiliano Pontil,Renaud Lambiotte,Cecilia Mascolo,Juan A Añel

doi:10.1371/journal.pone.0037027

Anastasios Noulas, Salvatore Scellato + Show 4 more

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https://doi.org/10.1371/journal.pone.0037027

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Abstract

The advent of geographic online social networks such as Foursquare, where users voluntarily signal their current location, opens the door to powerful studies on human movement. In particular the fine granularity of the location data, with GPS accuracy down to 10 meters, and the worldwide scale of Foursquare adoption are unprecedented. In this paper we study urban mobility patterns of people in several metropolitan cities around the globe by analyzing a large set of Foursquare users. Surprisingly, while there are variations in human movement in different cities, our analysis shows that those are predominantly due to different distributions of places across different urban environments. Moreover, a universal law for human mobility is identified, which isolates as a key component the rank-distance, factoring in the number of places between origin and destination, rather than pure physical distance, as considered in some previous works. Building on our findings, we also show how a rank-based movement model accurately captures real human movements in different cities.

Highlights

Since the seminal works of Ravenstein [1], the movement of people in space has been an active subject of research in the social and geographical sciences
A study of hundreds of thousands of cell phones in Los Angeles and New York demonstrate different characteristic trip lengths in the two cities [28]. This observation suggests either the absence of universal patterns in human mobility or the fact that physical distance is not a proper variable to express it. We address this problem by focusing on human mobility patterns in a large number of cities across the world
The empirical data on human movements provided by Foursquare and other location-based services allows for unprecedented analysis both in terms of scale and the information we have about the details of human movements

Summary

Introduction

Since the seminal works of Ravenstein [1], the movement of people in space has been an active subject of research in the social and geographical sciences It has been shown in almost every quantitative study and described in a broad range of models that a close relationship exists between mobility and distance. Human movements exhibit instead high levels of regularity and tend to be hindered by geographical distance The origin of this dependence of mobility on distance, and the formulation of quantitative laws explaining human mobility remains, an open question, the answer of which would lead to many applications, e.g. improve engineered systems such as cloud computing and location-based recommendations [2,3,4,5], enhance research in social networks [6,7,8,9] and yield insight into a variety of important societal issues, such as urban planning and epidemiology [10,11,12]. The first camp appears to have been favoured by practitioners on the grounds of computational ease [20], despite the fact that several statistical studies have shown that the concept of intervening opportunities is better at explaining a broad range of mobility data [21,22,23,24,25]

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