Human diffusion and city influence
Résumé
Cities are characterized by concentrating population, economic activity and services. However, not all cities are equal and hierarchy in terms of influence at local, regional or global scales naturally emerges. Traditionally, there have been important efforts to describe this hierarchy by indirect measures such the sharing of company headquarters, traffic by air, train or boats or economical exchanges. In this work, we take a different approach and introduce a method that uses geolocated Twitter information to quantify the impact of cities on rural or other urban areas. Since geolocated tweets are becoming a global phenomenon, the method can be applied at a world-wide scale. We focus on 58 cities and analyze the mobility patterns of people after visiting them for the first time. Cities such as Rome and Paris appear consistently as those with largest area covered by Twitter users after their visit and as those attracting visitors most diverse in origin. The study is also performed discerning users mobility by the contribution of locals and non-locals, which shows the relevance of the mixing ratio between them to have a global city. Finally, we focus on the mobility of users between cities and construct a network with the users flows between them. The network allows to analyze centrality defining it at a global and regional scale. The hierarchy of cities dramatically changes when referred only to urban users, with New York and London playing a predominant role. Ever since Christaller proposed the central place theory in the 30's [1], researchers have work to un-derstand the relations and competition between cities leading to the emergence of a hierarchy. Christaller envisioned an exclusive area surrounding each city to which it provided services such as markets, hospitals, schools, universities, etc. The services display differ-ent level of specialization, inducing thus a hierarchy among urban areas according to the type of services offered. In addition, this idea naturally brings an equidistant distribution of urban centers of similar category as long as no geographical constraints pre-vents it. Still, in the present globalized world the rela-tions between cities go beyond the mere geographical distance. In order to take into account this fact, it was necessary to introduce the concept of world city [2]. These are cities that concentrate economic warehouses like the headquarters of large multinational companies or global financial districts, of knowledge and innova-tion as the cutting edge technological firms or univer-sities, or political decision centers, and that play an eminent role of dominance over smaller, more local, counterparts. The concept of global cities is, never-theless, vague and needs further mathematical formal-ization. This is attained by means of the world city networks, in which each pair of cities is linked whether they share a common resource or interchange goods or people [3–5]. For instance, a link can be established if two cities share headquarters of the same company [5–7], if both are part of good production chains [8], interchange finance services [9], internet data [10] or if direct commercial or cargo flights or boats connect them [3, 11–13]. Centrality measures are then applied to the networks and a ranking of the cities raises. New York and London are, for example, the top rankers in many of these studies [4, 7, 12]. There are, however, inconsistencies in terms of the meaning and stability of the results obtained from different networks or with different centrality measures [12, 14].
Domaines
Statistiques [math.ST]
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