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https://doi.org/10.31219/osf.i...
Article . 2022 . Peer-reviewed
License: CC BY
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Bayesian explanations for persuasion

Authors: Andrew T Little;

Bayesian explanations for persuasion

Abstract

The central puzzle of persuasion is why a receiver would listen to a sender who they know is trying to change their beliefs or behavior. This article summarizes five approaches to solving this puzzle: (1) some messages are easier to send for those with favorable information ( costly signaling), (2) the sender and receiver have common interest, (3) the sender messages are verifiable information, (4) the sender cares about their reputation for competence/honesty, and (5) the sender can commit to a messaging strategy (often called ‘Bayesian Persuasion’). After reviewing these approaches with common notation, I discuss which provide insight into prominent empirical findings on campaigns, partisan media, and lobbying. While models focusing on commitment have rapidly become prominent (if not dominant) in the recent theoretical literature on persuasion in political science and economics, the insights they provide are primarily technical, and are not particularly well-suited to explaining most of these phenomena.

Country
United States
Related Organizations
Keywords

persuasion, Economics, Political Science, Political Science & Public Administration, Models and Methods, costly signaling, reputation, Cheap talk, Social and Behavioral Sciences, Political Economy, Economic Theory

  • BIP!
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    14
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
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    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Average
Top 10%
Green
hybrid