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We reviewed 555 papers published from 2016–2022 that presented misinformation to participants. We identified several trends in the literature—increasing frequency of misinformation studies over time, a wide variety of topics covered, and a significant focus on COVID-19 misinformation since 2020. We also identified several important shortcomings, including overrepresentation of samples from the United States and Europe and excessive emphasis on short-term consequences of brief, text-based misinformation.

In a pre-registered survey experiment with 2,009 conservative Republicans, we evaluated an intervention that framed accurate perceptions of information as consistent with a conservative political identity and conservative values (e.g., patriotism, respect for tradition, and religious purity). The intervention caused participants to report placing greater value on accuracy, and placing greater value on accuracy was correlated with successfully rating true headlines as more accurate than false headlines.

This study examined four fact checkers (Snopes, PolitiFact, Logically, and the Australian Associated Press FactCheck) using a data-driven approach. First, we scraped 22,349 fact-checking articles from Snopes and PolitiFact and compared their results and agreement on verdicts. Generally, the two fact checkers agreed with each other, with only one conflicting verdict among 749 matching claims after adjusting minor rating differences.

This study explores U.S. adults’ media consumption—in terms of the average bias and reliability of the media outlets participants report referencing—and the extent to which those participants hold inaccurate beliefs about COVID-19 and vaccination. Notably, we used a novel means of capturing the (left-right) bias and reliability of audiences’ media consumption, leveraging the Ad Fontes Media ratings of 129 news sources along each dimension.

Misinformation is ubiquitous; however, the extent and heterogeneity in public uptake of it remains a matter of debate. We address these questions by exploring Americans’ ability to recall prominent misinformation during the COVID-19 pandemic and the factors associated with accuracy perceptions of these claims.

Some people share misinformation accidentally, but others do so knowingly. To fully understand the spread of misinformation online, it is important to analyze those who purposely share it. Using a 2022 U.S. survey, we found that 14 percent of respondents reported knowingly sharing misinformation, and that these respondents were more likely to also report support for political violence, a desire to run for office, and warm feelings toward extremists.

We surveyed 150 academic experts on misinformation and identified areas of expert consensus. Experts defined misinformation as false and misleading information, though views diverged on the importance of intentionality and what exactly constitutes misinformation. The most popular reason why people believe and share misinformation was partisanship, while lack of education was one of the least popular reasons.

Older news users may be especially vulnerable to prior exposure effects, whereby news comes to be seen as more accurate over multiple viewings. I test this in re-analyses of three two-wave, nationally representative surveys in the United States (N = 8,730) in which respondents rated a series of mainstream, hyperpartisan, and false political headlines (139,082 observations).

As progress on vaccine rollout in the United States slowed down in Spring 2021, it became clear that anti-vaccine information posed a public health threat. Using text data from 5,613 distinct COVID misinformation stories and 70 anti-vaccination Facebook groups, we tracked highly salient keywords regarding anti-vaccine discourse across Twitter, thousands of news websites, and the Google and Bing search engines from May through June 2021, a key period when progress on vaccinations very clearly stalled.

TikTok provides opportunity for citizen-led debunking where users correct other users’ misinformation. In the present study (N=1,169), participants either watched and rated the credibility of (1) a misinformation video, (2) a correction video, or (3) a misinformation video followed by a correction video (“debunking”).