Source reliability and the continued influence effect of misinformation: A Bayesian network approach
- Jens Madsen, School of Geography and the Environment, University of Oxford, Oxford, United Kingdom
- Saoirse Connor Desai, Department of Psychology, City, University of London, London, United Kingdom
- Toby Pilditch, Department of Experimental Psychology, University College London, London, United Kingdom
AbstractMisinformation, and its impact on society, has become an increasingly topical field of study of late. A body of literature exists that suggests misinformation can retain an influence over beliefs despite subsequent retraction, known as the Continued Influence Effect (CIE). Researchers have argued this to be irrational. However, we show using a Bayesian formalism why this argument is overly assumptive, pointing to (previously overlooked) considerations of reliability of, and dependence between, misinforming and retracting sources. We demonstrate that lay reasoners intuitively endorse assumptions that demarcate CIE as a rational process, based on the fact misinformation precedes its retraction. Moreover, despite using established CIE materials, we further upturn the applecart by finding participants show CIE, and appropriately penalize the reliabilities of contradicting sources.
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