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Trump supported it?! A Bayesian source credibility model applied to appeals tospecific American presidential candidates’ opinions
Abstract
The credibility of politicians is crucial to their persuasivenessas election candidates. The paper applies a parameter-freeBaysian source credibility model (integrating trustworthinessand epistemic authority) in a real-life test predictingparticipants’ posterior belief in the goodness of an unnamedpolicy after a named candidate has publically supported orattacked it.Two studies test model predictions against policy supportand attack of five presidential candidates from the USA.Model predictions were measured against observed posteriorbelief in the goodness of the policy.The results strongly suggest the model captures essentialtraits of how participants update beliefs in policies givenappeals to a candidates’ support of attack. Further, individualdifferences suggest that people consider other factors thanthe ones elicited for the study. More studies into appeals tospecific candidates are warranted to construct more accuratemodels of the influence of source credibility on politicalreasoning.
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