(From left) Doctoral student Hannah Yamagata, research assistant professor Kushol Gupta, and postdoctoral fellow Marshall Padilla holding 3D-printed models of nanoparticles.
(Image: Bella Ciervo)
1 min. read
Public health promotion campaigns can be effective, but they do not tend to be efficient. Most are time-consuming, expensive, and reliant on the intuition of creative workers who design messages without a clear sense of what will spark behavioral change. A new study conducted by Penn’s Dolores Albarracín and Man-pui Sally Chan, government and community agencies, and researchers at the University of Illinois and Emory University, suggests that artificial intelligence (AI) can facilitate theory- and evidence-based message selection.
The research group, led by Albarracín, a social psychologist who is the Amy Gutmann Penn Integrates Knowledge University Professor with appointments in the School of Arts & Sciences and Annenberg School for Communication, developed a series of computational processes to automatically generate an HIV prevention and testing campaign for counties in the United States, using real-time social media as a source for messages.
The paper, whose lead author is Chan, a research associate professor at Penn’s Annenberg School for Communication, describes how the method provides a living repository of messages that can be selected based on the team’s theory and AI-generated data about messages that people and institutions circulate on social media.
Read more at Annenberg Public Policy Center.
From the Annenberg Public Policy Center
(From left) Doctoral student Hannah Yamagata, research assistant professor Kushol Gupta, and postdoctoral fellow Marshall Padilla holding 3D-printed models of nanoparticles.
(Image: Bella Ciervo)
Jin Liu, Penn’s newest economics faculty member, specializes in international trade.
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