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Social interactions vary in time and appear to be driven by intrinsicmechanisms, which in turn shape the emerging structure of the social network.Large-scale empirical observations of social interaction structure have becomepossible only recently, and modelling their dynamics is an actual challenge.Here we propose a temporal network model which builds on the framework ofactivity-driven time-varying networks with memory. The model also integrateskey mechanisms that drive the formation of social ties - social reinforcement,focal closure and cyclic closure, which have been shown to give rise tocommunity structure and the global connectedness of the network. We compare theproposed model with a real-world time-varying network of mobile phonecommunication and show that they share several characteristics fromheterogeneous degrees and weights to rich community structure. Further, thestrong and weak ties that emerge from the model follow similar weight-topologycorrelations as real-world social networks, including the role of weak ties.

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