Centrality in Dynamic Competition Networks

  • Anthony BonatoEmail author
  • Nicole Eikmeier
  • David F. Gleich
  • Rehan Malik
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 882)


Competition networks are formed via adversarial interactions between actors. The Dynamic Competition Hypothesis predicts that influential actors in competition networks should have a large number of common out-neighbors with many other nodes. We empirically study this idea as a centrality score and find the measure predictive of importance in several real-world networks including food webs, conflict networks, and voting data from Survivor.



The research for this paper was supported by grants from NSERC and Ryerson University. Gleich and Eikmeier acknowledge the support of NSF Awards IIS-1546488, CCF-1909528, the NSF Center for Science of Information STC, CCF-0939370, and the Sloan Foundation.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Anthony Bonato
    • 1
    Email author
  • Nicole Eikmeier
    • 2
  • David F. Gleich
    • 3
  • Rehan Malik
    • 1
  1. 1.Ryerson UniversityTorontoCanada
  2. 2.Grinnell CollegeGrinnellUSA
  3. 3.Purdue UniversityWest LafayetteUSA

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