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Nonlinear Dynamics of Networks
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Nonlinear Dynamics of Networks
CSIC Building (#406),
Seminar Room 4122.
Directions: home.cscamm.umd.edu/directions
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From human mobility to social networks and predictability
Albert-László Barabási
Northeastern University
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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 individual’s trajectory, we find can explore the underlying predictability of human mobility. |
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