Chris is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts and developed a real-time remote sensor of global happiness using messages from Twitter. Danforth co-runs the Computational Story Lab with Peter Dodds.

Curriculum Vitae (PDF)



Story Wrangler: a visual comparison of phrase popularity in 150 billion tweets

Hedonometer: a population scale measure of daily happiness


Research & Press

“Inside the lab that’s quantifying happiness”
Profile of our research group in Outside Magazine

“Has Twitter just had its saddest fortnight ever?”
Story on Hedonometer in Nature

“Instagram photos reveal predictive markers of depression”
Paper in EPJ Data Science, coverage by New York Times

“The emotional arcs of stories are dominated by six basic shapes”
Paper in EPJ Data Science, coverage by The Atlantic

“Human language reveals a universal positivity bias”
Paper in PNAS, coverage by New York Times

Areas of Expertise and/or Research

Chaos, Mathematical Modeling, Computational Social Science, Numerical Weather Prediction, Complex Systems, Computational Social Science


  • Ph.D., University of Maryland, College Park
  • B.S. in Mathematics & Physics, Bates College


  • (802) 656-3032
Office Location:

Innovation Hall E422

Courses Taught

  • MATH 122 - Linear Algebra
  • MATH 237 - Numerical Analysis
  • MATH 266 - Chaos, Fractals & Dynamical Systems
  • MATH 330 - Graduate Ordinary Differential Equations
  • MATH 382 - Graduate Seminar