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Nonlinear Dynamics of Networks

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From human mobility to social networks and predictability

Albert-László Barabási

Northeastern University


Abstract:   A range of applications, from predicting the spread of human and electronic viruses to city planning and resource management in mobile communications, depend on our ability to understand the mobility of individuals. Furthermore, the structure of social networks is also strongly influenced by the location of the individuals. Here I will study the mobility pattern of millions of anonymized mobile phone users to understand the statistical characteristics of human trajectories and the impact of the mobility on the underlying social network. I will show that human mobility follows reproducible scaling laws, which, however, deviate from the standard Levy flight or random walk based predictions. I will discuss a simple model that can account for the observed anomalies in the scaling behavior. Finally, as an application, I will show that by measuring the entropy of each individualís trajectory, we find can explore the underlying predictability of human mobility.

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