Identifying Influential Nodes Based on Community Structure to Speed up the Dissemination of Information in Complex Network

Abstract

Applying effective methods to identify important nodes in a complex network is highly invaluable. Recently, in a complex network, finding a powerful leader of the community to spread information quickly throughout the network is the concern of many researchers. In this paper, to identify influential nodes in a large and complex network, community-based mediator (CbM), which considers the entropy of a random walk from a node to each community is proposed as a metrics. CbM describes how the node is essential to connect two or more than two communities of the network. Correlations between CbM and other classical methods used to identify influential nodes are discussed. The performance of CbM is evaluated by susceptible-infected-recovered (SIR) model. In SIR model, the node is the most powerful node in the network, if the percentage of infected node is more while the node is used as the source of infection. Simulation results show that the proposed method performs better than the existing methods to spread information quickly and it can also introduce new influential nodes that other methods failed to identify.

Keywords

• Complex network
• community-based mediator
• influential nodes
• susceptible-infected-recovered model