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Bot Got Your Tongue? Social Learning with Timidity and Noise

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Abstract

Models of social learning conventionally assume that all actions are visible, whereas in reality, we can often choose whether or not to advertise our choices. Inthis paper, I study a model of sequential social learning in which social agents choose whether or not to let successors see their action, only wanting to do so if they are sufficiently confident in their choice (they are timid), and noise agents act randomly. I find that in sparse networks, this produces a form of unravelling to the effect that noise agents are overrepresented. This can damage learning to an arbitrary extent if social agents are sufficiently timid. In dense networks, however, no such unravelling occurs, and the combination of noise and timidity can facilitate complete learning even with bounded beliefs.

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  • John W.E. Cremin, 2025. "Bot Got Your Tongue? Social Learning with Timidity and Noise," AMSE Working Papers 2526, Aix-Marseille School of Economics, France.
    • Handle: RePEc:aim:wpaimx:2526
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    References listed on IDEAS

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    1. Guarino, Antonio & Harmgart, Heike & Huck, Steffen, 2011. "Aggregate information cascades," Games and Economic Behavior, Elsevier, vol. 73(1), pages 167-185, September.
    2. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
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