An improved pagerank for identifying the influential nodes based on resource allocation in directed networks

摘要

Identifying the influential nodes in directed networks is one of the most promising domains. In this paper, we present an improved PageRank based on the resource allocation (IPRA) method to identify the influential nodes. Comparing with the results of the Susceptible Infected Recovered (SIR) model for four real networks, the IPRA method could identify influential nodes more accurately than the PageRank and ClusterRank. Specially, in the US air line network, the Kendall's tau could be enhanced 700% when the spreading rate is 0.2. In the Email network, the Kendall's tau could be enhanced 850% when the spreading rate is 0.01.