Computational Psychology — Data Science for Good
I am a computational social scientist in psychology. Starting in early 2020, I will be an Assistant Professor in Psychology at Stanford, and a fellow at the Institute for Human-Centered Artificial Intelligence. I received my PhD and did a postdoc at the University of Pennsylvania with Martin Seligman. In 2011, I co-founded a big data psychology lab, the World Well-Being Project.
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. AI-based methods allow us to better understand these psychological phenomena, as well as 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 for public policy.
A key emphasis is on using these data and algorithms for good, to benefit well-being and health (and not sales).
Curriculum vitae (updated 09/2019).