Evolution models for dynamic networks

This paper proposes a mathematical framework for modelling the evolution of dynamic networks. Such framework allows the time analysis of the relationship between the dynamic laws and the network characterizing features (degree distribution, clustering coefficient, controllability indexes, etc.) providing new insight on the network properties. The framework also allows to relate and generalize existing inference procedures for modelling real world time evolving complex systems.