Persuading Communicating Voters

Kerman, Toygar; Tenev, Anastas P.

doi:10.2139/ssrn.3765527

Cited by 3 publications

(7 citation statements)

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“…Our main result has interesting implications to such a model. In particular, it immediately yields some results of [36] (see Subsection 3.3). Candogan [19] studies information spillover among receivers on a network in a general (not necessarily voting) context.…”

Section: Related Literaturementioning

confidence: 59%

“…We describe here works that diverge from this pattern and are, thus, related to our model of multi-channel persuasion. Kerman and Tenev [36] consider communicating voters: the voters (receivers) are located on a network; a politician (sender) tries to persuade them to vote for a proposal by sending them private signals; each voter ends up observing his own signal and the signals of his neighbours. Indeed, on social media, when a voter targeted by a politician shares the politician's message, his friends also see the message.…”

Section: Related Literaturementioning

confidence: 99%

“…In this subsection, we discuss the implications of our model to the setting of Kerman and Tenev [36] with receivers on a network. In particular, some of their results that show that certain communication structures are equivalent to private persuasion for specific utility functions immediately follow from our work.…”

Section: Receivers On a Networkmentioning

confidence: 99%

“…The intuitive reason is that no receiver's social ties are overshadowed in full by those of a friend. We exploit this fact to immediately deduce several results of [36], the original proofs of which were technically involved.…”

Section: Receivers On a Networkmentioning

confidence: 99%

“…Example 11. Suppose that G is a circle -a connected graph with all degrees equal to 2 (Proposition 5.4 from [36]). Provided that k > 3, Condition 10 holds and one can apply Corollary 8.…”

Section: Condition 10 For Everymentioning

confidence: 99%

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Multi-Channel Bayesian Persuasion

Babichenko¹,

Talgam-Cohen²,

Xu³

et al. 2021

Preprint

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The celebrated Bayesian persuasion model considers strategic communication between an informed agent (the sender) and uniformed decision makers (the receivers). The current rapidlygrowing literature assumes a dichotomy: either the sender is powerful enough to communicate separately with each receiver (a.k.a. private persuasion), or she cannot communicate separately at all (a.k.a. public persuasion). We propose a model that smoothly interpolates between the two, by introducing a natural multi-channel communication structure in which each receiver observes a subset of the sender's communication channels. This captures, e.g., receivers on a network, where information spillover is almost inevitable.We completely characterize when one communication structure is better for the sender than another, in the sense of yielding higher optimal expected utility universally over all prior distributions and utility functions. The characterization is based on a simple pairwise relation among receivers -one receiver information-dominates another if he observes at least the same channels. We prove that a communication structure M 1 is (weakly) better than M 2 if and only if every information-dominating pair of receivers in M 1 is also such in M 2 . We also provide an additive FPTAS for the optimal sender's signaling scheme when the number of states is constant and the graph of information-dominating pairs is a directed forest. Finally, we prove that finding an optimal signaling scheme under multi-channel persuasion is computationally hard for a general family of sender's utility functions that admit computationally tractable optimal signaling schemes under both public and private persuasion.

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Section: Related Literaturementioning

confidence: 59%

Section: Related Literaturementioning

confidence: 99%

Section: Receivers On a Networkmentioning

confidence: 99%

Section: Receivers On a Networkmentioning

confidence: 99%

“…Example 11. Suppose that G is a circle -a connected graph with all degrees equal to 2 (Proposition 5.4 from [36]). Provided that k > 3, Condition 10 holds and one can apply Corollary 8.…”

Section: Condition 10 For Everymentioning

confidence: 99%

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Multi-Channel Bayesian Persuasion

Babichenko¹,

Talgam-Cohen²,

Xu³

et al. 2021

Preprint

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Information design for weighted voting

Kerman,

Tenev

2024

Econ Theory

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We consider a sender who wishes to persuade multiple receivers to vote in favor of a proposal and sends them private correlated messages that are conditional on the true state of the world. The receivers share a common prior, wish to implement the outcome that matches the true state, and have homogeneous preferences. However, they are heterogeneous in their voting weights. We consider both behavioral and sophisticated voters. When voters are behavioral, public communication is optimal if and only if there is a veto player. For sophisticated voters, we establish lower bounds on the sender’s gain from persuasion for general voting quotas and show that the sender can often improve upon public communication. Finally, in an extension, we show that even when behavioral voters have heterogeneous prior beliefs, public communication is optimal if and only if there is a veto player.

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Bayesian Persuasion with Mediators

Arieli¹,

Babichenko²,

Sandomirskiy³

2022

Preprint

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A sender communicates with a receiver through a sequence of mediators. The sender is the only informed agent and the receiver is the only one taking an action. All the agents have their own utility functions, which depend on the receiver's action and the state.For any number of mediators, the sender's optimal value is characterized. For one mediator, the characterization has a clear geometric meaning of constrained concavification of the sender's utility, optimal persuasion requires the same number of signals as without mediators, and the presence of the mediator is never profitable for the sender. Surprisingly, the second mediator may improve the sender's utility; however, optimal persuasion with several mediators may require more signals. * We are grateful to Alexander Bloedel, Alessandro Pavan, and seminar participants at Bocconi University, Stony Brook Workshop on Strategic Communication and Learning, and Tel Aviv University for their comments.

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Persuading Communicating Voters

Cited by 3 publications

References 0 publications

Multi-Channel Bayesian Persuasion

Multi-Channel Bayesian Persuasion

Information design for weighted voting

Bayesian Persuasion with Mediators

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