Measuring large-scale happiness & health with social media
This talk will discuss our effort to quantify trends in a wide array of human behaviors using social media. It will showcase our Hedonometer http://hedonometer.org and its measurements of collective, dynamical patterns of happiness found in massive text corpora including Twitter, blogs, and song lyrics. Finally, I will also describe recent proof-of-concept studies using photographic data from Instagram to predictively screen for depression.
Chris Danforth is the Flint Professor of Mathematical, Natural, and Technical Sciences at the University of Vermont. Danforth has a BS in Math & Physics from Bates College and a PhD in Applied Mathematics from the University of Maryland. He has applied principles of chaos theory to improve the algorithms used to make weather forecasts, and built socio-technical instruments with social media to quantify human health & happiness. Along with Peter Dodds, he co-directs the Computational Story Lab, a group of applied mathematicians at the undergraduate, masters, phd, and postdoctoral level working on large-scale, system problems in many fields including sociology, nonlinear dynamics, networks, ecology, and physics. His research has been covered by the New York Times, Science Magazine, and the BBC among others. Descriptions of his projects are available at his website: http://uvm.edu/~cdanfort