I am a computational social scientist in psychology, an Assistant Professor in Psychology, and a Shriram Faculty Fellow at the Institute for Human-Centered Artificial Intelligence. I direct the Computational Psychology and Well-Being lab. In 2011, I co-founded what is now a consortium of labs that combines NLP with psychology, AI, and public health, the World Well-Being Project (wwbp.org). I received my Ph.D. and did a postdoc at the University of Pennsylvania.
I use Facebook and Twitter 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. A.I.-based methods allow us to better understand these psychological phenomena, as well as 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.
Real-time measurement of population mental health is becoming particularly critical in the aftermath of COVID-19, and to track the impact of disruptive events like the murder of George Floyd.
A key emphasis of this computational work is to use these data and algorithms for good, to benefit well-being and health.