From calls to communities: a model for time-varying social networks

Social interactions vary in time and appear to be driven by intrinsic mechanisms thatshape the emergent structure of social networks. Large-scale empirical observations ofsocial interaction structure have become possible only recently, and modelling theirdynamics is an actual challenge. Here we propose a temporal network model which builds onthe framework of activity-driven time-varying networks with memory. Themodel integrates key mechanisms that drive the formation of social ties – socialreinforcement, focal closure and cyclicclosure, which have been shown to give rise to community structure andsmall-world connectedness in social networks. We compare the proposed model with areal-world time-varying network of mobile phone communication, and show that they shareseveral characteristics from heterogeneous degrees and weights to rich communitystructure. Further, the strong and weak ties that emerge from the model follow similarweight-topology correlations as real-world social networks, including the role of weakties.