In communication networks structure and dynamics are tightly coupled. The
structure controls the flow of information and is itself shaped by the
dynamical process of information exchanged between nodes. In order to reconcile
structure and dynamics, a generic model, based on the local interaction between
nodes, is considered for the communication in large social networks. In
agreement with data from a large human organization, we show that the flow is
non-Markovian and controlled by the temporal limitations of individuals. We
confirm the versatility of our model by predicting simultaneously the
degree-dependent node activity, the balance between information input and
output of nodes and the degree distribution. Finally, we quantify the
limitations to network analysis when it is based on data sampled over a finite
period of time.Comment: Physical Review Letter, accepted (5 pages, 4 figures
