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Misinformation research often draws optimistic conclusions, with fact-checking, for example, being established as an effective means of reducing false beliefs. However, it rarely considers the details of socioeconomic disparities that often shape who is most vulnerable to science misinformation. Historical and systemic inequalities have fostered mistrust in institutions, limiting access to credible information, for example, when Black patients distrust public health guidance due to past medical racism.

This study investigates the impact of educational interventions and feedback on users’ ability to detect manipulated images on social media, addressing a gap in research that has primarily focused on algorithmic approaches. Through a pre-registered randomized and controlled experiment, we found that feedback and educational content significantly improved participants’ ability to detect manipulated images on social media.

While understanding how social media algorithms operate is essential to protect oneself from misinformation, such understanding is often unevenly distributed. This study explores the algorithmic knowledge gap both within and between countries, using national surveys in the United States (N = 1,415), the United Kingdom (N = 1,435), South Korea (N = 1,798), and Mexico (N = 784).

Although prebunking games have shown promise in Western and English-speaking contexts, there is a notable lack of research on such interventions in countries of the Global South. In response to this gap, we developed Gali Fakta, a new kind of media literacy game specifically tailored for an Indonesian audience.

A growing number of educational interventions have shown that students can learn the strategies fact checkers use to efficiently evaluate online information. Measuring the effectiveness of these interventions has required new approaches to assessment because extant measures reveal too little about the processes students use to evaluate live internet sources.

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).

This paper examines strategies for making misinformation interventions responsive to four communities of color. Using qualitative focus groups with members of four non-profit organizations, we worked with community leaders to identify misinformation narratives, sources of exposure, and effective intervention strategies in the Asian American Pacific Islander (AAPI), Black, Latino, and Native American communities.

Through the lens of one of the fastest-growing international fandoms, this study explores everyday misinformation in the context of networked online environments. Findings show that fans experience a range of misinformation, similar to what we see in other political, health, or crisis contexts.

It has been widely argued that social media users with low digital literacy—who lack fluency with basic technological concepts related to the internet—are more likely to fall for online misinformation, but surprisingly little research has examined this association empirically. In a large survey experiment involving true and false news posts about politics and COVID-19, we found that digital literacy is indeed an important predictor of the ability to tell truth from falsehood when judging headline accuracy.