The mathematical study of the small-world concept has fostered quite some interest, showing that small-world features can be identified for some abstract classes of networks. However, passing to real complex systems, as for instance transportation networks, shows a number of new problems that make current analysis impossible. In this paper we show how a more refined kind of analysis, relying on transportation efficiency, can in fact be used to overcome such problems, and to give precious insights on the general characteristics of real transportation networks, eventually providing a picture where the small-world comes back as underlying construction principle. The characterization of the structural properties of the underlying network is a very crucial issue to understand the function of a complex system [1]. For example, the structure of a social network affects spreading of information, fashions, rumors but also of epidemics over the network; the topological properties of a computer network (Internet, the World Wide Web) affect the efficiency of the communication. Only recently the accessibility of databases of real networks and the availability of powerful computers have made possible a series of empirical studies [2] [3] [4] [5] [6] . In [2] Watts and Strogatz have shown that the connection topology of some (social, biological and technological) networks is neither completely regular nor completely random [2] . Watts and Strogatz have named these networks, that are somehow in between regular and random networks, small worlds, in analogy with the small-world phenomenon observed in social systems [7] . The mathematical characterization of the small-world behavior is based on the evaluation of two quantities, the characteristic path
In one of the earliest network-based studies of urban transportation systems, Latora and Marichiori investigated the Boston subway network and highlighted the small-world properties and local and global efficiency of the network REF .
Is the Boston Subway a Small-World Network?
Physica A-statistical Mechanics and Its Applications
Mathematics Physics