What misinformation is
Because "fake news" is vague and often used as a political insult, researchers prefer the framework of information disorder. Wardle and Derakhshan (2017) distinguished three types by falseness and intent to harm.
- Misinformation: false information shared without intent to harm, such as health myths passed on in good faith.
- Disinformation: false information deliberately created and spread to cause harm or gain advantage, such as fabricated stories aimed at elections.
- Malinformation: genuine information shared to cause harm, such as leaking private details.
Formats range from entirely fabricated articles to images stripped of context, manipulated video, satire mistaken for fact and deepfakes.
Confirmation bias
Confirmation bias is the tendency to seek, remember and favor information that supports existing beliefs or hypotheses while ignoring or discounting contrary information. Nickerson (1998) described it as a ubiquitous phenomenon in everyday and professional life.
- Wason's 2-4-6 task (1960): asked to discover the rule that "2-4-6" fits, most participants tested only sequences consistent with their own hypothesis (for example 8-10-12 for "even numbers rising by two") and rarely tried sequences that could disprove it. The actual rule was simply "ascending numbers."
- Biased search, interpretation and memory: people read the same evidence in their own favor and recall supporting cases more easily.
- Motivated reasoning: beliefs tied to identity or group membership resist contrary evidence most strongly. The discomfort of conflicting information is also explained by cognitive dissonance theory.
Intelligence analysts' analysis of competing hypotheses and behavioral finance both treat reducing confirmation bias as a central task.
How they interact
- Selective exposure: people choose outlets and channels that match their views and scrutinize falsehoods there less.
- Filter bubbles and echo chambers: recommendation algorithms keep serving congenial content, and like-minded users amplify the same claims among themselves.
- Faster spread: analyzing about 126,000 rumor cascades on Twitter, Vosoughi, Roy and Aral (2018) found that false news spread farther, faster and more broadly than truth, especially when novel and emotionally arousing.
- Lazy thinking: Pennycook and Rand (2019) reported that susceptibility to fake news is better explained by a failure to reason carefully than by partisan motivation, showing that confirmation bias is not the whole story.
Limits of correction and remedies
Lewandowsky et al. (2012) reviewed the continued influence effect: misinformation keeps shaping reasoning even after correction. Explaining why a claim is wrong and offering an alternative account works better than simply saying "that's false."
- Fact-checking: news organizations and independent bodies verify and publish the accuracy of claims.
- Prebunking: warning people about manipulation techniques in advance builds resistance, like a "psychological vaccine."
- Media literacy: habits such as checking sources, finding the original, cross-checking other outlets and distrusting emotionally charged headlines.
- Platforms and regulation: algorithmic transparency, labeling and down-ranking of false content are debated, balanced against free expression and fears of censorship.
References
- Wason, P. C. (1960). On the failure to eliminate hypotheses in a conceptual task. Quarterly Journal of Experimental Psychology, 12(3), 129–140.
- Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175–220.
- Lewandowsky, S., Ecker, U. K. H., Seifert, C. M., Schwarz, N., & Cook, J. (2012). Misinformation and its correction: Continued influence and successful debiasing. Psychological Science in the Public Interest, 13(3), 106–131.
- Wardle, C., & Derakhshan, H. (2017). Information Disorder: Toward an Interdisciplinary Framework for Research and Policy Making (Council of Europe report DGI(2017)09). Strasbourg: Council of Europe.
- Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science, 359(6380), 1146–1151.
- Pennycook, G., & Rand, D. G. (2019). Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning. Cognition, 188, 39–50.