Bot Got Your Tongue? Social Learning with Endogenous Action Visibility

John Cremin

Working Papers from HAL

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. In this 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 have reputation concerns), 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' reputation concerns are sufficiently strong. In dense networks, however, no such unravelling occurs, and the combination of noise and reputation concerns can facilitate complete learning even with bounded beliefs.

Keywords: Sequential Social Learning; Endogenous Social Networks; Network Theory; Information Economics (search for similar items in EconPapers)
Date: 2025-12-17
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