Research

We examine what drives belief in inaccurate information, why people sometimes do not change their belief even in the face of good corrective evidence, and how corrections can be designed to maximize impact.

We are particularly interested in studying health misinformation, with a specific focus on cancer. We are interested in measuring the prevalence of cancer misinformation on social media, how people make judgements of source credibility for disreputable cancer sources, and the cognitive mechanisms underlying belief and belief updating of cancer misinformation.

Our lab examines the spread and impact of misinformation on social media platforms. We analyze how misinformation propagates through social networks, the role of algorithms in amplifying false information, and potential interventions to mitigate misinformation’s impact online.

We investigate how memory limits belief revision. Most recently we have focused on the association between memory for corrective information and a phenomenon called “belief regression”. This is where individuals update their beliefs extremely well initially, but belief returns towards pre-correction belief levels over time.

A backfire effect is where a correction leads to an individual increasing their belief in the very misconception the correction is aiming to rectify. We examine barriers to measuring backfire effects (such as reliability), and discuss approaches to improving measurement and design.

Insight into one’s own cognitive abilities is one important aspect of metacognition. We examine not only whether people can discern between true and false news, but whether they are aware of this ability.

In the current information ecosystem, it is extremely easy for dubious sources to claim to be experts. We examine how legitimate communicators can discredit these sources and redirect individuals towards evidence-based information.