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Complex Network Influence Evaluation based on extension of Grueblers Equation

It is greatly significant in evaluating nodes Influence ranking in complex networks. Over the years, many researchers present different measures for quantifying node interconnectedness within networks. Therefore, this paper introduces a centrality measure called Tr-centrality which focuses on using the node triangle structure and the node neighborhood information to define the strength of a node, which is defined as the summation of Grueblers Equation of nodes one-hop triangle neighborhood to the number of all the edges in the subgraph. Furthermore, we socially consider it as the local trust of a node. To verify the validity of Tr-centrality, we apply it to four real-world networks with different densities and shapes and Tr-centrality has proven to yield better results.

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