Complex Network Node Centrality Measurement Based on Multiple Attributes

Finding key nodes in complex networks plays an important role in improving the robustness of the network. In view of the limitations of traditional methods, a method of node centrality measurement based on multiple attributes (NCMMA) is proposed in this paper. Firstly, the centrality measurement of complex network nodes is formulated, the method of evaluating the accuracy of node centrality measurement is given. Secondly, the local characteristic indicator, global characteristic indicator and emergence characteristic indicator of complex network are defined, then, NCMMA is designed to synthesize these indicators. Finally, nodes ranking experiments and propagation experiments are performed on ARPA-NET(Advanced Research Project Agency NET), scale-free network and small world network, to compare NCMMA and the traditional methods. The results show that the proposed NCMMA is feasible and the key nodes obtained by the NCMMA have higher influence than key nodes obtained by traditional methods in the propagation experiments based on Susceptible-Infected(SI) epidemic model.