The Bias‐and‐Expertise Model: A Bayesian Network Model of Political Source Characteristics

TL;DR

This paper introduces a new model that explains how people update their beliefs based on a source's perceived bias and expertise in political contexts.

Contribution

The model integrates bias and expertise in a Bayesian Network, which is novel in political cognition research.

Findings

The model accurately predicts belief updates in response to source testimony.

Results are validated across two studies, including a preregistered replication.

Perceptions of bias and expertise significantly influence credibility judgments.

Abstract

Perceptions of source credibility may play a role in major societal challenges like political polarization and the spread of misinformation as citizens disagree over which sources of political information are credible and sometimes trust untrustworthy sources. Cognitive scientists have developed Bayesian Network models of how people integrate perceptions of source credibility when learning from information provided by sources, but these models do not involve the crucial source characteristic in politics: bias. Biased sources make claims that align with a particular political agenda, whether or not they are true. We present a novel Bayesian Network model which integrates perceptions of a source's bias as well as their expertise. We demonstrate the model's validity for predicting how people will update beliefs and perceptions of bias and expertise in response to testimony across two studies, the second being a preregistered conceptual replication and extension of the first.

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