Random graph models for temporal processes in social networks

Abstract

We generalize the graphical modeling approach of p* social influence models to develop discrete time models for the temporal evolution of social networks. Plausible general processes pertaining to network evolution are broadly discussed as a basis for across-time dependence assumptions. Systematic temporal processes are construed as effects that are homogeneous across the network, and that reflect dynamics inherent in a particular social relation. Any one actor cannot control these dynamics, especially given that non-dyadic configurations may be implicated, for instance, tendencies for various triadic configurations to be constructed or to collapse of over time. Non-systematic processes, on ..