The Computational Social Listening Lab utilizes machine learning, deep learning, and natural language processing methods to uncover insights about health attitudes, behaviors, and outcomes, with a particular focus on health disparities and mental health and wellbeing. This team has developed computational models to measure and understand topics as wide-ranging as life satisfaction, ADHD, misinformation exposure, COVID-19 symptoms, and friendship using large-scale user-generated text, image, and mobile sensor data.
Currently, the lab’s work focuses on global mental health, vaccine acceptance, and firearms safety. Priorities include:
-Digital mental health
-Cultural and racial heterogeneity in health behaviors and outcomes
-Developing precision public health messaging