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Communicating with Anecdotes

Author

Listed:
  • Nika Haghtalab
  • Nicole Immorlica
  • Brendan Lucier
  • Markus Mobius
  • Divyarthi Mohan

Abstract

We study a communication game between a sender and receiver where the sender has access to a set of informative signals about a state of the world. The sender chooses one of her signals, called an ``anecdote'' and communicates it to the receiver. The receiver takes an action, yielding a utility for both players. Sender and receiver both care about the state of the world but are also influenced by a personal preference so that their ideal actions differ. We characterize perfect Bayesian equilibria when the sender cannot commit to a particular communication scheme. In this setting the sender faces ``persuasion temptation'': she is tempted to select a more biased anecdote to influence the receiver's action. Anecdotes are still informative to the receiver but persuasion comes at the cost of precision. This gives rise to ``informational homophily'' where the receiver prefers to listen to like-minded senders because they provide higher-precision signals. In particular, we show that a sender with access to many anecdotes will essentially send the minimum or maximum anecdote even though with high probability she has access to an anecdote close to the state of the world that would almost perfectly reveal it to the receiver. In contrast to the classic Crawford-Sobel model, full revelation is a knife-edge equilibrium and even small differences in personal preferences will induce highly polarized communication and a loss in utility for any equilibrium. We show that for fat-tailed anecdote distributions the receiver might even prefer to talk to poorly informed senders with aligned preferences rather than a knowledgeable expert whose preferences may differ from her own. We also show that under commitment differences in personal preferences no longer affect communication and the sender will generally report the most representative anecdote closest to the posterior mean for common distributions.

Suggested Citation

  • Nika Haghtalab & Nicole Immorlica & Brendan Lucier & Markus Mobius & Divyarthi Mohan, 2022. "Communicating with Anecdotes," Papers 2205.13461, arXiv.org.
  • Handle: RePEc:arx:papers:2205.13461
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    References listed on IDEAS

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