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Ranking Competitors Using Degree-Neutralized Random Walks

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  • Seungkyu Shin
  • Sebastian E Ahnert
  • Juyong Park

Abstract

Competition is ubiquitous in many complex biological, social, and technological systems, playing an integral role in the evolutionary dynamics of the systems. It is often useful to determine the dominance hierarchy or the rankings of the components of the system that compete for survival and success based on the outcomes of the competitions between them. Here we propose a ranking method based on the random walk on the network representing the competitors as nodes and competitions as directed edges with asymmetric weights. We use the edge weights and node degrees to define the gradient on each edge that guides the random walker towards the weaker (or the stronger) node, which enables us to interpret the steady-state occupancy as the measure of the node's weakness (or strength) that is free of unwarranted degree-induced bias. We apply our method to two real-world competition networks and explore the issues of ranking stabilization and prediction accuracy, finding that our method outperforms other methods including the baseline win–loss differential method in sparse networks.

Suggested Citation

  • Seungkyu Shin & Sebastian E Ahnert & Juyong Park, 2014. "Ranking Competitors Using Degree-Neutralized Random Walks," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-13, December.
  • Handle: RePEc:plo:pone00:0113685
    DOI: 10.1371/journal.pone.0113685
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    References listed on IDEAS

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    1. Richard J. Williams & Neo D. Martinez, 2000. "Simple rules yield complex food webs," Nature, Nature, vol. 404(6774), pages 180-183, March.
    2. Raymond Stefani, 1997. "Survey of the major world sports rating systems," Journal of Applied Statistics, Taylor & Francis Journals, vol. 24(6), pages 635-646.
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    Cited by:

    1. Seungkyu Shin & Juyong Park, 2018. "On-Chart Success Dynamics Of Popular Songs," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(03n04), pages 1-18, May.
    2. Clive B Beggs & Alexander J Bond & Stacey Emmonds & Ben Jones, 2019. "Hidden dynamics of soccer leagues: The predictive ‘power’ of partial standings," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-28, December.

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