Communicating with Anecdotes (Extended Abstract)

Authors Nika Haghtalab, Nicole Immorlica, Brendan Lucier, Markus Mobius, Divyarthi Mohan

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Author Details

Nika Haghtalab
  • University of California, Berkeley, CA, USA
Nicole Immorlica
  • Microsoft Research, Cambridge, MA, USA
Brendan Lucier
  • Microsoft Research, Cambridge, MA, USA
Markus Mobius
  • Microsoft Research, Cambridge, MA, USA
Divyarthi Mohan
  • Tel Aviv University, Israel


Parts of this work were done when the authors visited the Simons Institute for the Theory of Computing and when Haghtalab and Mohan were employed at Microsoft Research.

Cite AsGet BibTex

Nika Haghtalab, Nicole Immorlica, Brendan Lucier, Markus Mobius, and Divyarthi Mohan. Communicating with Anecdotes (Extended Abstract). In 15th Innovations in Theoretical Computer Science Conference (ITCS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 287, pp. 57:1-57:2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


We study a communication game between a sender and receiver. The sender chooses one of her signals about the state of the world (i.e., an anecdote) and communicates it to the receiver who takes an action affecting both players. The sender and receiver both care about the state of the world but are also influenced by personal preferences, so their ideal actions can differ. We characterize perfect Bayesian equilibria. The sender faces a temptation to persuade: she wants to select a biased anecdote to influence the receiver’s action. Anecdotes are still informative to the receiver (who will debias at equilibrium) but the attempt to persuade 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. Communication becomes polarized when the sender is an expert with access to many signals, with the sender choosing extreme outlier anecdotes at equilibrium (unless preferences are perfectly aligned). This polarization dissipates all the gains from communication with an increasingly well-informed sender when the anecdote distribution is heavy-tailed. Experts therefore face a curse of informedness: receivers will prefer to listen to less-informed senders who cannot pick biased signals as easily.

Subject Classification

ACM Subject Classification
  • Theory of computation → Algorithmic game theory and mechanism design
  • Applied computing → Economics
  • Communication game
  • Equilibrium
  • Polarization
  • Signalling


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