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Inferring the network topology from the dynamics is a fundamental problemwith wide applications in geology, biology and even counter-terrorism. Based onthe propagation process, we present a simple method to uncover the networktopology. The numerical simulation on artificial networks shows that our methodenjoys a high accuracy in inferring the network topology. We find the infectionrate in the propagation process significantly influences the accuracy, and eachnetwork is corresponding to an optimal infection rate. Moreover, the methodgenerally works better in large networks. These finding are confirmed in bothreal social and nonsocial networks. Finally, the method is extended to directednetworks and a similarity measure specific for directed networks is designed.

Inferring network topology via the propagation process