We have released a new preprint dealing with the analysis of temporal networks of human contacts: Activity clocks: spreading dynamics on temporal networks of human contact. In this manuscript, we show how spreading processes are an efficient investigation tool of contact networks by focusing on the arrival time distributions of such processes. When computed in terms of “activity clocks” inherent to each node of the network, these distributions are shown to exhibit a very robust behavior. We define hierarchies of null and generative models of time-varying networks and show that the empirical patterns can be understood in terms of heterogeneous inter-event time distributions coupled with heterogeneous numbers of events per edge. We also show, both empirically and by using a synthetic dataset, that significant deviations from the generic behavior can be caused by the presence of edge classes with strong activity correlations.
