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The Fragility of Social Learning with Noisy Messages

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  • Matthew O. Jackson
  • Suraj Malladi
  • David McAdams

Abstract

We examine how agents learn when information from original sources only reaches them after noisy relay. A receiver learns if and only if they have access to sufficiently many chains of noisy relay and they perfectly understand the noise process. However, even slight uncertainty over message mutation rates makes learning from long chains impossible, no matter how many independent sources are accessed.

Suggested Citation

  • Matthew O. Jackson & Suraj Malladi & David McAdams, 2026. "The Fragility of Social Learning with Noisy Messages," Papers 2608.18283, arXiv.org.
    • Handle: RePEc:arx:papers:2608.18283
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    References listed on IDEAS

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    1. T Renee Bowen & Danil Dmitriev & Simone Galperti, 2023. "Learning from Shared News: When Abundant Information Leads to Belief Polarization," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(2), pages 955-1000.
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