IDEAS home Printed from https://ideas.repec.org/p/snv/dp2009/2014114.html
   My bibliography  Save this paper

How Variability in Individual Patterns of Behavior Changes the Structural Properties of Networks

Author

Listed:
  • Somayeh Koohborfardhaghighi

    () (Technology Management, Economics, and Policy Program, College of Engineering, Seoul National University)

  • Jorn Altmann

    () (Technology Management, Economics, and Policy Program, College of Engineering, Seoul National University)

Abstract

Dynamic processes in complex networks have received much attention. This attention reflects the fact that dynamic processes are the main source of changes in the structural properties of complex networks (e.g., clustering coefficient and average shortest-path length). In this paper, we develop an agent-based model to capture, compare, and explain the structural changes within a growing social network with respect to individuals’ social characteristics (e.g., their activities for expanding social relations beyond their social circles). According to our simulation results, the probability increases that the network’s average shortest-path length is between 3 and 4, if most of the dynamic processes are based on random link formations. That means, in Facebook, the existing average shortest path length of 4.7 can even shrink to smaller values. Another result is that, if the node increase is larger than the link increase when the network is formed, the probability increases that the average shortest-path length is between 4 and 8.

Suggested Citation

  • Somayeh Koohborfardhaghighi & Jorn Altmann, 2014. "How Variability in Individual Patterns of Behavior Changes the Structural Properties of Networks," TEMEP Discussion Papers 2014114, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Jun 2014.
  • Handle: RePEc:snv:dp2009:2014114
    as

    Download full text from publisher

    File URL: ftp://147.46.237.98/DP-114.pdf
    File Function: First version, 2014
    Download Restriction: no

    References listed on IDEAS

    as
    1. Somayeh Koohborfardhaghighi & Jorn Altmann, 2014. "How Placing Limitations on the Size of Personal Networks Changes the Structural Properties of Complex Networks," TEMEP Discussion Papers 2014110, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Jan 2014.
    2. 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.
    3. Andrea Galeotti & Sanjeev Goyal & Matthew O. Jackson & Fernando Vega-Redondo & Leeat Yariv, 2010. "Network Games," Review of Economic Studies, Oxford University Press, vol. 77(1), pages 218-244.
    4. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 1999. "Mean-field theory for scale-free random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 272(1), pages 173-187.
    5. Somayeh Koohborfardhaghighi & Jorn Altmann, 2014. "How Structural Changes in Complex Networks Impact Organizational Learning Performance," TEMEP Discussion Papers 2014111, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Mar 2014.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Network Properties; Network Growth Models; Small World Theory; Network Science; Simulation; Clustering Coefficient; Complex Networks.;

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:snv:dp2009:2014114. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Jorn Altmann). General contact details of provider: http://edirc.repec.org/data/tesnukr.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.