Reading Between the Tweets: Social Technologies for Predicting and Changing Health Behavior

Sean D. Young, Ph.D.

Speaker: Sean D. Young, Ph.D., M.S.

Executive Director, University of California Institute for Prediction Technology

Associate Professor, Departments of Emergency Medicine and Informatics University of California, Irvine

Date: November 02, 2021 - 1:00 p.m. ET to 2:00 p.m. ET

Location: Virtual

NIH videocast >


Sean D. Young, Ph.D., M.S., is executive director of the University of California Institute for Prediction Technology (UCIPT) and associate professor (a split appointment) in the Department of Emergency Medicine, School of Medicine, and the Department of Informatics, Donald Bren School of Information and Computer Sciences, at the University of California, Irvine. UCIPT brings together researchers across University of California campuses from a wide variety of disciplines to study how social “big data,” machine learning, and data mining can be used to predict real-world events. Dr. Young is also the author of a bestselling book, Stick With It: A Scientifically Proven Process for Changing Your Life—for Good. He is a member of the Board on Population Health and Public Health Practice within the National Academies of Science, Engineering, and Medicine.

Dr. Young’s research focuses on: (1) using social big data to monitor and predict public health issues such as HIV, substance use, suicide, and public safety/crime; and (2) designing and testing technologies to address public health and medical issues among at-risk populations such as African Americans, Latinxs, or men who have sex with men (MSM). He earned his doctorate in psychology and his master’s degrees in psychology and in health services research from Stanford University. NIH funders of his research include NCCIH and the National Institute of Neurological Disorders and Stroke (through the NIH HEAL [Helping to End Addiction Long-termSM] Initiative), as well as the National Institute on Drug Abuse, National Center for Advancing Translational Sciences, National Institute of Allergy and Infectious Diseases, and National Institute of Mental Health. Dr. Young was a recipient of the Ruth L. Kirschstein National Research Service Award and a T32 fellowship.

Learning Objectives:

  1. Learn how artificial intelligence modeling on social data might be integrated into public health surveillance efforts.
  2. Describe the Harnessing Online Peer Education (HOPE) online community intervention and its acceptability and effectiveness as a method for changing health behaviors among racial, ethnic, and sexual minorities. 
  3. Give examples of potential implementation and policy issues related to use of technologies and technology data in public health surveillance and interventions.* 

*CME credit is not available for this event.

Reasonable Accommodation:

To request sign language interpretation or other reasonable accommodations to participate, contact the NCCIH Clearinghouse at or 1-888-644-6226 or the Federal Relay (1-800-877-8339).