The Bias‐and‐Expertise Model
A Bayesian Network Model of Political Source Characteristics
Datos Bibliográficos
| ID | 7150256 |
|---|---|
| Autores | David J Young (0000-0002-2707-8284, Department of Psychology University of Cambridge, autor de correspondencia), Lee De‐wit (0000-0003-3048-2875), Lee H De‐wit (Department of Psychology University of Cambridge) |
| Año | 2025 |
| Volumen | 49 |
| Número | 11 |
| Páginas | e70141-e70141 |
| Fecha de publicación | 2025-11-01 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Cognitive Science (JOURNAL) |
| Identificadores de la revista | ISSN: 0364-0213 • E-ISSN: 1551-6709 |
| Editorial | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/cogs.70141 |
| PMID | 41261846 |
| OpenAlex | W4416387854 |
| Idioma | EN |
| Referencias citadas | 62 |
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
Bayesian network · Bayesian probability · Confirmation bias · Credibility · Misinformation · Perception · Politics · Source credibility · Computational and Text Analysis Methods · Educational Strategies and Epistemologies · Misinformation and Its Impacts
Bayesian Data Analysis
At Least Bias Is Bipartisan
The Politically Motivated Reasoning Paradigm, Part 1
When Disagreement Gets Ugly
The Partisan Brain
Defining the Enemy
Rational argument, rational inference
How Computational Modeling Can Force Theory Building in Psychological Science
Socially adaptive belief
Influences of Position Justification on Perceived Bias
Belief polarization can be caused by disagreements over source independence
Conservatism in human information processing
Seeing the subjective as objective
Media Bias and Reputation
Partisan Bias and the Bayesian Ideal in the Study of Public Opinion
The Influence of Source Credibility on Communication Effectiveness
Voter Reasoning Bias When Evaluating Statements from Female and Male Political Candidates
Beyond the Running Tally
Misperceptions About Perceptual Bias
Partisan Gaps in Political Information and Information‐Seeking Behavior
Influences of source bias that differ from source untrustworthiness
| Velocidad de citación | historical |
|---|---|
| Altamente citado | No |