Human Behavior: When you search the Internet to verify false information, you may be convinced that the information is correct Nature | Nature Portfolio

One study cites the results of a study that found that people who were tasked with determining the veracity of fake news using a search engine were more likely to be convinced of the veracity of the information.naturePublished in Follow-up experiments suggested that the reason for these results was that the quality of information participants obtained through online searches was poor. The results suggest that digital literacy programs that help people searching online evaluate the quality of search results are essential.

As misinformation continues to grow and political divisions widen, seeking the truth may become more complicated than a quick online search. Although research has been done on how misinformation spreads on social media, little attention has been paid to how people use search engines to fact-check misinformation. But this did not happen.

Kevin Aslett and colleagues conducted a study in which participants (3,006 people) living in the United States rated the accuracy of news articles published within 48 hours before participating in the study. In the first study, participants who were encouraged to search for false information online were 19% more likely to rate false information as true than those who were not encouraged to do so. This test has been performed a total of five times with consistent results.

The study also found evidence that participants who evaluated news articles through online searches were more likely to find supporting evidence from lower-quality sources. Aslett and others refer to this situation as a “data vacuum.” These results suggest that when using search engines to evaluate news articles, confidence in their accuracy may increase if the news articles come from low-quality sources.

Aslett et al note that the findings highlight the need to develop and implement robust digital literacy programs that focus on the use of search engines.

doi:10.1038/s41586-023-06883-y

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