Relevance theory for mapping cognitive biases in fact-checking: an argumentative approach

Area of Science:

• Information Science
• Cognitive Psychology
• Journalism Studies

Background:

• Distinguishing information from misinformation is crucial in the digital age.
• Fact-checkers combat fake news but are susceptible to cognitive biases from overload and time pressure.
• Mitigating biases can improve fact-check quality, audience trust, and defense against disinformation.

Purpose of the Study:

• To identify cognitive biases in fact-checking, their triggers, and reasoning levels.
• To propose a novel approach based on relevance theory and the argumentum model of topics.
• To develop standards for mitigating biases in fact-checking processes.

Main Methods:

• A multimethod case study combining a semi-automatic literature review.
• A fact-checking simulation involving 12 news practitioners.
• An online survey with 40 journalists and fact-checkers.

Main Results:

• Identified biases triggered by relevance by effort and relevance by effect.
• Developed a taxonomy of cognitive biases within the fact-checking decision-making process.
• Demonstrated a method to map cognitive biases in reasoning.

Conclusions:

• The proposed approach effectively identifies and maps cognitive biases in fact-checking.
• Insights can inform training to enhance fact-checkers' critical thinking skills.
• Improving fact-checker training enhances the quality and trustworthiness of fact-checking practices.