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Mining Important Nodes in Directed Weighted Complex Networks

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  • Yunyun Yang
  • Gang Xie
  • Jun Xie

Abstract

In complex networks, mining important nodes has been a matter of concern by scholars. In recent years, scholars have focused on mining important nodes in undirected unweighted complex networks. But most of the methods are not applicable to directed weighted complex networks. Therefore, this paper proposes a Two-Way-PageRank method based on PageRank for further discussion of mining important nodes in directed weighted complex networks. We have mainly considered the frequency of contact between nodes and the length of time of contact between nodes. We have considered the source of the nodes (in-degree) and the whereabouts of the nodes (out-degree) simultaneously. We have given node important performance indicators. Through numerical examples, we analyze the impact of variation of some parameters on node important performance indicators. Finally, the paper has verified the accuracy and validity of the method through empirical network data.

Suggested Citation

  • Yunyun Yang & Gang Xie & Jun Xie, 2017. "Mining Important Nodes in Directed Weighted Complex Networks," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-7, March.
    • Handle: RePEc:hin:jnddns:9741824
    DOI: 10.1155/2017/9741824
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    Cited by:

    1. Yang, Ruicheng & Xing, Weize & Hou, Shuxia, 2020. "Evaluating the risk factors influencing foreign direct investment in Mongolia's mining sector: A complex network approach," Emerging Markets Review, Elsevier, vol. 43(C).
    2. Hiroki Noguchi & Takuma Nishizawa & Masaaki Fuse, 2021. "A method to characterize the social cascading damage processes of disasters using media information," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(1), pages 231-247, May.

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