2014/09/30 by Hao Liao, Liao, Hao, An Zeng +1
Computer Science · Mathematics · Physics and Astronomy · #Applications (stat.AP) #FOS: Computer and information sciences #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI) #cs.SI #physics.soc-ph #stat.AP
paper · pdf · doi:10.48550/arxiv.1409.8481
8 pages, 5 figures, 2 tables
arxiv created 2014/09/30 · arxiv updated 2014/10/01
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.