Data Science for Good.

We use NLP and large language data from the social web (Facebook, Twitter, Reddit) to measure the psychological states of large populations and individuals, to determine the thoughts, emotions, and behaviors that drive illness, depression, or support well-being.

Large-scale text analysis allows us to understand these psychological phenomena better (as well as many other traits and stats), and to measure their expression unobtrusively and at scale for large populations.

This is especially relevant for the measurement of subjective well-being for populations around the world—in places where no traditional measures are available with sufficient spatial and temporal resolution to measure the impact of economic or social disruptions, or to inform public policy.

With the recent advances in Large Language Models, we now have a new technology to screen patients for mental health conditions, deliver mental health care, and deliver well-being interventions, which our lab is exploring in ongoing work.

We are part of the World Well-Being Project consortium which we co-founded in 2011, and part of the Stanford Institute for Human-Centered Artificial Intelligence.