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Measuring centrality by a generalization of degree

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  • Csató, László

Abstract

Network analysis has emerged as a key technique in communication studies, economics, geography, history and sociology, among others. A fundamental issue is how to identify key nodes in a network, for which purpose a number of centrality measures have been developed. This paper proposes a new parametric family of centrality measures called generalized degree. It is based on the idea that a relationship to a more interconnected node contributes to centrality in a greater extent than a connection to a less central one. Generalized degree improves on degree by redistributing its sum over the network with the consideration of the global structure. Application of the measure is supported by a set of basic properties. A sufficient condition is given for generalized degree to be rank monotonic, excluding counter-intuitive changes in the centrality ranking after certain modifications of the network. The measure has a graph interpretation and can be calculated iteratively. Generalized degree is recommended to apply besides degree since it preserves most favorable attributes of degree, but better reflects the role of the nodes in the network and has an increased ability to distinguish between their importance.

Suggested Citation

  • Csató, László, 2015. "Measuring centrality by a generalization of degree," Corvinus Economics Working Papers (CEWP) 2015/02, Corvinus University of Budapest.
  • Handle: RePEc:cvh:coecwp:2015/02
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    2. Ausloos, Marcel, 2024. "Hierarchy selection: New team ranking indicators for cyclist multi-stage races," European Journal of Operational Research, Elsevier, vol. 314(2), pages 807-816.
    3. Marijana Zekić-Sušac & Rudolf Scitovski & Goran Lešaja, 2018. "CEJOR special issue of Croatian Operational Research Society," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(3), pages 531-534, September.
    4. Tibor Csendes & Csanád Imreh & József Temesi, 2017. "Editorial," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(4), pages 739-741, December.

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    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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