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Rather than assuming that people are motivated to fact-check, we investigated the process that people go through when and if they encounter political misinformation. Using a digital diary method, we asked 38 participants to collect examples of political misinformation during Australia’s 2025 federal election and explain why they determined it to be misinformation (n = 254).

Boosting psychological defences against misleading content online is an active area of research, but transition from the lab to real-world uptake remains a challenge. We developed a 19-second prebunking video about emotionally manipulative content and showed it as a Story Feed ad to N = 375,597 Instagram users in the United Kingdom.

What if knowing how social media algorithms work doesn’t make you a more responsible digital citizen, but a more cynical one? A new survey of U.S. young adults finds that while higher algorithmic awareness and knowledge are linked to greater concerns about misinformation and filter bubbles, individuals with greater algorithmic awareness and knowledge are less likely to correct misinformation or engage with opposing viewpoints on social media—possibly reflecting limited algorithmic agency.

In response to the escalating threat of misinformation, social media platforms have introduced a wide range of interventions aimed at reducing the spread and influence of false information. However, there is a lack of a coherent macro-level perspective that explains how these interventions operate independently and collectively.

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.