Abstract
Thomas C. Schelling introduced a simple mathematical model to address the phenomenon of social segregation as a consequence of a natural evolution of elementary local rules. This model became a good framework to understand how local rules, like the selection of a better neighborhood for life, can produce macro-behaviors, like segregation in a population with different kind of individuals. In this work, with the aid of the Schelling's model, we characterize the dynamical evolution of segregation in random networks; analyze the performance of some segregation indices and the dynamics of this model for various network degrees. Finally, we provide probabilistic arguments to explain quantitatively the behavior of the dynamic of Schelling's segregation model in networks.
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