  Node similarity is a significant property driving the growth of real
networks. In this paper, based on the observed spreading results we apply the
node similarity metrics to reconstruct propagation networks. We find that the
reconstruction accuracy of the similarity metrics is strongly influenced by the
infection rate of the spreading process. Moreover, there is a range of
infection rate in which the reconstruction accuracy of some similarity metrics
drops to nearly zero. In order to improve the similarity-based reconstruction
method, we finally propose a temporal similarity metric to take into account
the time information of the spreading. The reconstruction results are
remarkably improved with the new method.

Physics and Society;Social and Information Networks;Applications