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On Decay Centrality

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  • Tsakas Nikolas

    (Department of Economics, University of Cyprus, PO Box 20537, 1678Nicosia, Cyprus)

Abstract

We establish a relationship between decay centrality and two widely used measures of centrality, namely degree and closeness. We show that for low values of the decay parameter the nodes with maximum decay centrality also have maximum degree, whereas for high values of the decay parameter they also maximize closeness. For intermediate values, we provide sufficient conditions that allow the comparison of decay centrality of different nodes and we show via numerical simulations that in the vast majority of networks, the nodes with maximum decay centrality are characterized by a threshold on the decay parameter below which they belong to the set of nodes with maximum degree and above which they belong to the set of nodes with maximum closeness. We also propose a simple rule of thumb that ensures a nearly optimal choice with very high probability.

Suggested Citation

  • Tsakas Nikolas, 2019. "On Decay Centrality," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 19(1), pages 1-18, January.
    • Handle: RePEc:bpj:bejtec:v:19:y:2019:i:1:p:18:n:6
    DOI: 10.1515/bejte-2017-0010
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    References listed on IDEAS

    as
    1. Jackson, Matthew O. & Wolinsky, Asher, 1996. "A Strategic Model of Social and Economic Networks," Journal of Economic Theory, Elsevier, vol. 71(1), pages 44-74, October.
    2. Nikolas Tsakas, 2014. "Optimal influence under observational learning," Gecomplexity Discussion Paper Series 4, Action IS1104 "The EU in the new complex geography of economic systems: models, tools and policy evaluation", revised Nov 2014.
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    Cited by:

    1. Tsakas, Nikolas, 2024. "Optimal influence under observational learning," Mathematical Social Sciences, Elsevier, vol. 128(C), pages 41-51.

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    More about this item

    Keywords

    decay centrality; centrality measures; networks;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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