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Identifying influential spreaders by weight degree centrality in complex networks

Author

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  • Liu, Yang
  • Wei, Bo
  • Du, Yuxian
  • Xiao, Fuyuan
  • Deng, Yong

Abstract

The problem of identifying influential spreaders in complex networks has attracted much attention because of its great theoretical significance and wide application. In this paper, we propose a successful ranking method for identifying the influential spreaders. The proposed method measures the spreading ability of nodes based on their degree and their ability of spreading out. We also use a tuning weight parameter, which is always associated with the property of the networks such as the assortativity, to regulate the weight between the degree and the ability of spreading out. To test the effectiveness of the proposed method, we conduct the experiments on several synthetic networks and real-world networks. The results show that the proposed method outperforms the existing well-known ranking methods.

Suggested Citation

  • Liu, Yang & Wei, Bo & Du, Yuxian & Xiao, Fuyuan & Deng, Yong, 2016. "Identifying influential spreaders by weight degree centrality in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 86(C), pages 1-7.
    • Handle: RePEc:eee:chsofr:v:86:y:2016:i:c:p:1-7
    DOI: 10.1016/j.chaos.2016.01.030
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    References listed on IDEAS

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    3. Chun-Wei Chen & Neng-Tang Huang & Hsien-Sheng Hsiao, 2022. "The Construction and Application of E-Learning Curricula Evaluation Metrics for Competency-Based Teacher Professional Development," Sustainability, MDPI, vol. 14(14), pages 1-22, July.
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    7. Wang, Min & Li, Wanchun & Guo, Yuning & Peng, Xiaoyan & Li, Yingxiang, 2020. "Identifying influential spreaders in complex networks based on improved k-shell method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).

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