Using Local Improved Structural Holes Method to Identify Key Nodes in Complex Networks

Abstract

In complex networks, it is significant to rank the nodes according to their importance. In this paper we present an algorithm based on an improved Structural Holes method to identify the key nodes of a complex network. Since our approach does not need to consider the global structure of a network but only consider the number of one node's neighbors and it's next nearest neighbors, the nodes importance can be calculated with local information of a complex network. Experimental results of ARPA net show that our method is better than some important ranking measures such as between ness, degree or closeness. It is very useful for evaluating the key nodes in large scale and complicated networks, in which evaluation of nodes importance is almost impossible to calculate with global information.