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Network structure and social learning

Network structure and social learning We describe results from Dasaratha and He [DH21a] and Dasaratha and He [DH20] about how network structure influences social learning outcomes. These papers share a tractable sequential model that lets us compare learning dynamics across networks. With Bayesian agents, incomplete networks can generate informational confounding that makes learning arbitrarily inefficient. With naive agents, related forces can lead to mislearning. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGecom Exchanges Association for Computing Machinery

Network structure and social learning

Dasaratha, Krishna; He, Kevin
ACM SIGecom Exchanges , Volume 19 (2): 6 – Dec 6, 2021
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Publisher
Association for Computing Machinery
Copyright
Copyright © 2021 Copyright is held by the owner/author(s)
ISSN
1551-9031
eISSN
1551-9031
DOI
10.1145/3505156.3505163
Publisher site
See Article on Publisher Site

Abstract

We describe results from Dasaratha and He [DH21a] and Dasaratha and He [DH20] about how network structure influences social learning outcomes. These papers share a tractable sequential model that lets us compare learning dynamics across networks. With Bayesian agents, incomplete networks can generate informational confounding that makes learning arbitrarily inefficient. With naive agents, related forces can lead to mislearning.

Journal

ACM SIGecom Exchanges – Association for Computing Machinery

Published: Dec 6, 2021

Keywords: bayesian learning

References

  • Bayesian learning in social networks
    Acemoglu, Daron; Dahleh, Munther A; Lobel, Ilan; Ozdaglar, Asuman
  • A simple model of herd behavior
    Banerjee, Abhijit V
  • A theory of fads, fashion, custom, and cultural change as informational cascades
    Bikhchandani, Sushil; Hirshleifer, David; Welch, Ivo
  • Network structure and naive sequential learning
    Dasaratha, Krishna; He, Kevin
  • Aggregative efficiency of bayesian learning in networks
    Dasaratha, Krishna; He, Kevin
  • An experiment on network density and sequential learning
    Dasaratha, Krishna; He, Kevin
  • Naive herding in rich-information settings
    Eyster, Erik; Rabin, Matthew
  • Rational groupthink
    Harel, Matan; Mossel, Elchanan; Strack, Philipp; Tamuz, Omer
  • On the efficiency of social learning
    Rosenberg, Dinah; Vieille, Nicolas