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On decay centrality


  • Nikolas Tsakas


We establish a relationship between decay centrality and two widely used and computationally cheaper measures of centrality, namely degree and closeness centrality. 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 of the decay parameter, we perform an extensive set of simulations on random networks and find that maximum degree or closeness are good proxies for maximum decay centrality. In particular, in the vast majority of simulated 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. The threshold values vary with the characteristics of the network. Moreover, nodes with maximum degree or closeness are highly ranked in terms of decay centrality even when they are not maximizing it. The latter analysis allows us to propose a simple rule of thumb that ensures a nearly optimal choice with very high probability.

Suggested Citation

  • Nikolas Tsakas, 2016. "On decay centrality," University of Cyprus Working Papers in Economics 04-2016, University of Cyprus Department of Economics.
  • Handle: RePEc:ucy:cypeua:04-2016

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    References listed on IDEAS

    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. repec:adr:anecst:y:2007:i:86 is not listed on IDEAS
    3. 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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    More about this item


    decay centrality; centrality measures; networks;

    JEL classification:

    • 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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