Finding important nodes based on community structure and degree of neighbor nodes to disseminate information in complex networks

Applying effective methods to identify important nodes in a large and complex network is highly invaluable. Recently, in a large and complex network, finding a powerful node in the community to spread information throughout the network is the concern of many researchers. In this paper, to identify powerful nodes in a large and complex network, community-based important node (CBIN) method, which reflects on the community structure of the network and degree of neighbor nodes is proposed as a metrics. CBIN considers a random walk from a node to each community and degree of neighbor nodes. Then, CBIN describes how many influential friends the node has and how the node is essential to connect two or more than two communities of the network. The performance of CBIN is evaluated by Susceptible-Infected (SI) model. Simulation results on a real network show that the proposed method performs better than the existing methods to spread information in the network.