IDEAS home Printed from https://ideas.repec.org/p/ucy/cypeua/04-2016.html
   My bibliography  Save this paper

On decay centrality

Author

Listed:
  • Nikolas Tsakas

Abstract

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
    as

    Download full text from publisher

    File URL: https://papers.econ.ucy.ac.cy/RePEc/papers/04-16.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Eunae Yoo & Elliot Rabinovich & Bin Gu, 2020. "The Growth of Follower Networks on Social Media Platforms for Humanitarian Operations," Production and Operations Management, Production and Operations Management Society, vol. 29(12), pages 2696-2715, December.
    2. Rajgopal Kannan & Lydia Ray & Sudipta Sarangi, 2007. "The structure of information networks," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 30(1), pages 119-134, January.
    3. Nicolas Carayol & Pascale Roux & Murat Yıldızoğlu, 2008. "In search of efficient network structures: the needle in the haystack," Review of Economic Design, Springer;Society for Economic Design, vol. 11(4), pages 339-359, February.
    4. Mikaela Backman & Charlie Karlsson, 2016. "Determinants of self-employment among commuters and non-commuters," Papers in Regional Science, Wiley Blackwell, vol. 95(4), pages 755-774, November.
    5. Bloch, Francis & Jackson, Matthew O., 2007. "The formation of networks with transfers among players," Journal of Economic Theory, Elsevier, vol. 133(1), pages 83-110, March.
    6. Finneran, Lisa & Kelly, Morgan, 2003. "Social networks and inequality," Journal of Urban Economics, Elsevier, vol. 53(2), pages 282-299, March.
    7. Herings, P. Jean-Jacques & Mauleon, Ana & Vannetelbosch, Vincent, 2020. "Matching with myopic and farsighted players," Journal of Economic Theory, Elsevier, vol. 190(C).
    8. Babus, Ana & Parlatore, Cecilia, 2022. "Strategic fragmented markets," Journal of Financial Economics, Elsevier, vol. 145(3), pages 876-908.
    9. Vasileios Zikos, 2010. "R&D Collaboration Networks in Mixed Oligopoly," Southern Economic Journal, John Wiley & Sons, vol. 77(1), pages 189-212, July.
    10. Liu, Xiaodong & Patacchini, Eleonora & Zenou, Yves & Lee, Lung-Fei, 2011. "Criminal Networks: Who is the Key Player?," Research Papers in Economics 2011:7, Stockholm University, Department of Economics.
    11. Magnan, Nicholas & Spielman, David J. & Lybbert, Travis J. & Gulati, Kajal, 2015. "Leveling with friends: Social networks and Indian farmers' demand for a technology with heterogeneous benefits," Journal of Development Economics, Elsevier, vol. 116(C), pages 223-251.
    12. Cabrales, Antonio & Calvó-Armengol, Antoni & Zenou, Yves, 2011. "Social interactions and spillovers," Games and Economic Behavior, Elsevier, vol. 72(2), pages 339-360, June.
    13. Tesfatsion, Leigh, 1998. "Ex Ante Capacity Effects in Evolutionary Labor Markets with Adaptive Search," ISU General Staff Papers 199810010700001046, Iowa State University, Department of Economics.
    14. Bich, Philippe & Teteryatnikova, Mariya, 2023. "On perfect pairwise stable networks," Journal of Economic Theory, Elsevier, vol. 207(C).
    15. Zhepeng Li & Xiao Fang & Xue Bai & Olivia R. Liu Sheng, 2017. "Utility-Based Link Recommendation for Online Social Networks," Management Science, INFORMS, vol. 63(6), pages 1938-1952, June.
    16. Grabisch, Michel & Rusinowska, Agnieszka, 2011. "Influence functions, followers and command games," Games and Economic Behavior, Elsevier, vol. 72(1), pages 123-138, May.
    17. Eboli, Mario, 2013. "A flow network analysis of direct balance-sheet contagion in financial networks," Kiel Working Papers 1862, Kiel Institute for the World Economy (IfW Kiel).
    18. Jean-François Caulier & Ana Mauleon & Vincent Vannetelbosch, 2013. "Contractually stable networks," International Journal of Game Theory, Springer;Game Theory Society, vol. 42(2), pages 483-499, May.
    19. Baumann, Leonie, 2021. "A model of weighted network formation," Theoretical Economics, Econometric Society, vol. 16(1), January.
    20. Falk Armin & Kosfeld Michael, 2012. "It's all about Connections: Evidence on Network Formation," Review of Network Economics, De Gruyter, vol. 11(3), pages 1-36, September.

    More about this item

    Keywords

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

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ucy:cypeua:04-2016. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://www.ucy.ac.cy/econ/?lang=en .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.