Detection of Non-self-correcting Nature of Information Cascade

  • Shintaro MoriEmail author
  • Masafumi Hino
  • Masato Hisakado
  • Taiki Takahashi
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)


We propose a method of detecting non-self-correcting information cascades in experiments in which subjects choose an option sequentially by observing the choices of previous subjects. The method uses the correlation function C(t) between the first and the \(t+1\)th subject’s choices. C(t) measures the strength of the domino effect, and the limit value \(c\equiv \lim _{t\rightarrow \infty }C(t)\) determines whether the domino effect lasts forever \((c>0)\) or not \((c=0)\). The condition \(c>0\) is an adequate condition for a non-self-correcting system, and the probability that the majority’s choice remains wrong in the limit \(t\rightarrow \infty \) is positive. We apply the method to data from two experiments in which T subjects answered two-choice questions: (i) general knowledge questions (\(T_{avg}=60\)) and (ii) urn-choice questions (\(T=63\)). We find \(c>0\) for difficult questions in (i) and all cases in (ii), and the systems are not self-correcting.


Correct Choice Difficult Question Private Signal Domino Effect Wrong Option 
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This work was supported by Grant-in-Aid for Challenging Exploratory Research 25610109.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Shintaro Mori
    • 1
    Email author
  • Masafumi Hino
    • 2
  • Masato Hisakado
    • 3
  • Taiki Takahashi
    • 4
    • 5
  1. 1.Department of PhysicsKitasato UniversitySagamiharaJapan
  2. 2.NEC CorporationMinato-kuJapan
  3. 3.Financial Services AgencyChiyoda-kuJapan
  4. 4.Department of Behavioral Science, Faculty of LettersHokkaido UniversitySapporoJapan
  5. 5.Center for Experimental Research in Social SciencesHokkaido UniversitySapporoJapan

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