2 hours ago
Ritwik Banerjee, research assistant professor of computer science.Scroll through Instagram or X long enough, and you’ll see it — a reel insisting that “fruits are citrus, so you shouldn’t eat them with milk,” a thread warning “protein shakes wreck kidney function,” a carousel promising “this workout routine will fix your PCOS in 30 days.” Every third post seems to offer a health hack, often backed by a chart, a DOI link, and just enough scientific language to sound convincing.
But behind those posts is a tangle of dense scientific research that few people ever read.
“How do we get from what scientists actually know, to what people are saying online?” asked Ritwik Banerjee, research assistant professor of computer science at Stony Brook University. “Right now, that bridge is very noisy. Claims slip, get simplified or just made up.”
Yet most of us never click through to read the original paper. We assume the citation is honest, especially when it confirms what we want to believe. Banerjee said, “We need reliable tools to trace what’s real.”
Banerjee, working with graduate student Parth Manish Thapliyal, undergraduate students Ritesh Sunil Chavan and Samridh Samridh, and Chaoyuan Zuo at Nankai University, developed a solution in response to the challenge called CheckThat! 2025, organized under the CLEF conference held in Madrid, Spain. Their research attempts to bridge this information gap using AI: when a social media post invokes “science,” can we design an automated system to figure out which research article, if any, actually matches the claim?
Read the full story by Ankita Nagpal at the AI Innovation Institute website.
