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Node influence identification via resource allocation dynamics

Author

Listed:
  • Shu-Jiao Ma

    (Business School, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China)

  • Zhuo-Ming Ren

    (Business School, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China)

  • Chun-Ming Ye

    (Business School, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China)

  • Qiang Guo

    (Business School, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China)

  • Jian-Guo Liu

    (Business School, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China)

Abstract

Identifying the node influence in complex networks is an important task to optimally use the network structure and ensure the more efficient spreading in information. In this paper, by taking into account the resource allocation dynamics (RAD) and thek-shell decomposition method, we present an improved method namely RAD to generate the ranking list to evaluate the node influence. First, comparing with the epidemic process results for four real networks, the RAD method could identify the node influence more accurate than the ones generated by the topology-based measures including the degree,k-shell, closeness and the betweenness. Then, a growing scale-free network model with tunable assortative coefficient is introduced to analyze the effect of the assortative coefficient on the accuracy of the RAD method. Finally, the positive correlation is found between the RAD method and thek-shell values which display an exponential form. This work would be helpful for deeply understanding the node influence of a network.

Suggested Citation

  • Shu-Jiao Ma & Zhuo-Ming Ren & Chun-Ming Ye & Qiang Guo & Jian-Guo Liu, 2014. "Node influence identification via resource allocation dynamics," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 25(11), pages 1-13.
    • Handle: RePEc:wsi:ijmpcx:v:25:y:2014:i:11:n:s012918311450065x
    DOI: 10.1142/S012918311450065X
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    References listed on IDEAS

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    1. Carol Y. Lin, 2008. "Modeling Infectious Diseases in Humans and Animals by KEELING, M. J. and ROHANI, P," Biometrics, The International Biometric Society, vol. 64(3), pages 993-993, September.
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    Cited by:

    1. Zhong, Lin-Feng & Shang, Ming-Sheng & Chen, Xiao-Long & Cai, Shi-Ming, 2018. "Identifying the influential nodes via eigen-centrality from the differences and similarities of structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 77-82.

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