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A novel method of evaluating key nodes in complex networks

Canshi Zhu, Xiaoyang Wang and Lin Zhu

Chaos, Solitons & Fractals, 2017, vol. 96, issue C, 43-50

Abstract: In order to evaluate the influence of nodes in complex networks, a new method is advanced of evaluating key nodes in complex networks, in combination with the “structural hole” theory and closeness centrality of nodes, through defining and applying the influence matrix of nodes’ “structural holes” in response to the limitations of existing methods. The “structural hole” theory gives a comprehensive consideration of the node degree as well as information about topological relations with its neighbors, whereas the closeness centrality of nodes is a reflection of the node's global information. The “structural holes” influence matrix in degree reflects the node's local and global information. So a more proper evaluation standard is established for influence of nodes and a simulation analysis is made of different-scale networks. The results of such analyses show that the method can not only make an exact assessment of the influence of nodes, but also obtain ideal evaluation results from actual complex networks of different scale.

Keywords: Complex networks; Structural hole; Closeness centrality; Influence matrix (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:96:y:2017:i:c:p:43-50

DOI: 10.1016/j.chaos.2017.01.007

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