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This study introduces a computational model explaining why people believe conspiracy theories. It highlights how prior beliefs, evidence, and the high cost of rejecting a theory influence endorsement, even over accuracy.

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Area of Science:

  • Social Sciences
  • Psychology
  • Computational Social Science

Background:

  • Research on conspiracy theories is rapidly expanding within the social sciences.
  • Understanding the psychological drivers of conspiracy theory endorsement is crucial.

Purpose of the Study:

  • To introduce a novel computational model for the psychological processes underlying support for conspiracy theories.
  • To explore the role of motivated reasoning and the cost of rejection in conspiracy endorsement.
  • To examine the social conditions that foster conspiracy theory success in contemporary Western societies.

Main Methods:

  • Development of a computational model integrating prior beliefs, novel evidence, and expected consequences.
  • Analysis of the interplay between psychological factors and social context.
  • Application of the model to understand conspiracy theories in Western societies.

Main Results:

  • Conspiracy theory endorsement is influenced by prior beliefs, evidence, and crucially, the expected consequences of rejection.
  • The model suggests that theories may be favored due to the high cost of disproving them, not necessarily their evidential support.
  • Motivated reasoning plays a significant role in the selection and maintenance of conspiracy beliefs.

Conclusions:

  • A computational approach can effectively elucidate the socio-psychological dynamics driving the appeal of conspiracy theories.
  • The model provides a framework for understanding why inaccurate beliefs can persist and gain traction.
  • Understanding these psychological mechanisms is key to addressing the societal impact of conspiracy theories.