Abstract

Assessing the importance of a node in a network is often very important. It can show the core of a network and provide guidance to decision makers. This paper combines the relevant characteristics of social networks, and proposes to use related smoothing weight factors to balance the clustering coefficient of nodes in the network, and to measure the importance of nodes as an important index. Experiments show that the importance of the nodes evaluated by this method is closer to the real situation. The importance of all nodes in the entire network is more consistent with the power law distribution.

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