IDEAS home Printed from https://ideas.repec.org/p/koe/wpaper/1529.html
   My bibliography  Save this paper

Trend-driven information cascades on random networks

Author

Listed:
  • Teruyoshi Kobayashi

    () (Graduate School of Economics, Kobe University)

Abstract

No abstract is available for this item.

Suggested Citation

  • Teruyoshi Kobayashi, 2015. "Trend-driven information cascades on random networks," Discussion Papers 1529, Graduate School of Economics, Kobe University.
  • Handle: RePEc:koe:wpaper:1529
    as

    Download full text from publisher

    File URL: http://www.econ.kobe-u.ac.jp/RePEc/koe/wpaper/2015/1529.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Charles D. Brummitt & Teruyoshi Kobayashi, 2015. "Cascades in multiplex financial networks with debts of different seniority," Papers 1501.05400, arXiv.org, revised May 2015.
    2. Kobayashi, Teruyoshi, 2014. "A model of financial contagion with variable asset returns may be replaced with a simple threshold model of cascades," Economics Letters, Elsevier, vol. 124(1), pages 113-116.
    3. Centola, Damon & Eguíluz, Víctor M. & Macy, Michael W., 2007. "Cascade dynamics of complex propagation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(1), pages 449-456.
    4. Gai, Prasanna & Haldane, Andrew & Kapadia, Sujit, 2011. "Complexity, concentration and contagion," Journal of Monetary Economics, Elsevier, vol. 58(5), pages 453-470.
    5. M. Catanzaro & R. Pastor-Satorras, 2005. "Analytic solution of a static scale-free network model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 44(2), pages 241-248, March.
    6. Duncan J. Watts & Peter Sheridan Dodds, 2007. "Influentials, Networks, and Public Opinion Formation," Journal of Consumer Research, Oxford University Press, vol. 34(4), pages 441-458, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fabio Caccioli & Paolo Barucca & Teruyoshi Kobayashi, 2018. "Network models of financial systemic risk: a review," Journal of Computational Social Science, Springer, vol. 1(1), pages 81-114, January.

    More about this item

    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:koe:wpaper:1529. 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: (Kimiaki Shirahama) The email address of this maintainer does not seem to be valid anymore. Please ask Kimiaki Shirahama to update the entry or send us the correct email address. General contact details of provider: http://edirc.repec.org/data/fekobjp.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.