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PhysarumSpreader: A New Bio-Inspired Methodology for Identifying Influential Spreaders in Complex Networks

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  • Hongping Wang
  • Yajuan Zhang
  • Zili Zhang
  • Sankaran Mahadevan
  • Yong Deng

Abstract

Identifying influential spreaders in networks, which contributes to optimizing the use of available resources and efficient spreading of information, is of great theoretical significance and practical value. A random-walk-based algorithm LeaderRank has been shown as an effective and efficient method in recognizing leaders in social network, which even outperforms the well-known PageRank method. As LeaderRank is initially developed for binary directed networks, further extensions should be studied in weighted networks. In this paper, a generalized algorithm PhysarumSpreader is proposed by combining LeaderRank with a positive feedback mechanism inspired from an amoeboid organism called Physarum Polycephalum. By taking edge weights into consideration and adding the positive feedback mechanism, PhysarumSpreader is applicable in both directed and undirected networks with weights. By taking two real networks for examples, the effectiveness of the proposed method is demonstrated by comparing with other standard centrality measures.

Suggested Citation

  • Hongping Wang & Yajuan Zhang & Zili Zhang & Sankaran Mahadevan & Yong Deng, 2015. "PhysarumSpreader: A New Bio-Inspired Methodology for Identifying Influential Spreaders in Complex Networks," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-21, December.
    • Handle: RePEc:plo:pone00:0145028
    DOI: 10.1371/journal.pone.0145028
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    References listed on IDEAS

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    1. Linyuan Lü & Yi-Cheng Zhang & Chi Ho Yeung & Tao Zhou, 2011. "Leaders in Social Networks, the Delicious Case," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-9, June.
    2. Pei Wang & Jinhu Lü & Xinghuo Yu, 2014. "Identification of Important Nodes in Directed Biological Networks: A Network Motif Approach," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-15, August.
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