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Can Invalid Information Be Ignored When It Is Detected?

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Even when people detect misinformation, they may still incorporate it into their beliefs. This study shows that quantitative misinformation exposure biases judgment, even with warnings.

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belief updatingestimationjudgmentmisinformationopen dataoutliers

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Area of Science:

  • Cognitive Psychology
  • Social Psychology
  • Information Science

Background:

  • Social media facilitates rapid information spread, increasing exposure to misinformation.
  • Individuals may unknowingly use inaccurate quantitative data when forming beliefs.

Purpose of the Study:

  • To investigate if individuals can ignore misreported quantitative information.
  • To determine if people's estimates are biased by invalid data they identify.

Main Methods:

  • Five experiments with 815 US adults recruited via Amazon Mechanical Turk.
  • Participants estimated means from Gaussian distributions containing outlier (invalid) values.
  • Investigated effects of visual warnings and task variations on ignoring misinformation.

Main Results:

  • Participants successfully detected outliers in quantitative data.
  • Estimates remained biased towards the invalid outlier values, despite detection.
  • Warnings and varied scenarios did not fully prevent biased estimations.

Conclusions:

  • Individuals may integrate detected misinformation into their belief formation.
  • Cognitive biases persist even when individuals attempt to disregard invalid quantitative information.
  • Understanding these biases is crucial for combating misinformation effects.