Abstract
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.
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Acknowledgments
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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Bonato, A., Eikmeier, N., Gleich, D.F., Malik, R. (2020). Centrality in Dynamic Competition Networks. In: Cherifi, H., Gaito, S., Mendes, J., Moro, E., Rocha, L. (eds) Complex Networks and Their Applications VIII. COMPLEX NETWORKS 2019. Studies in Computational Intelligence, vol 882. Springer, Cham. https://doi.org/10.1007/978-3-030-36683-4_9
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