In this talk, I will report on a wide array of findings obtained through our real-time, remote-sensing, non-invasive, text-based `hedonometer'---an instrument for measuring positivity in written expression, housed online at hedonometer.org. I'll show how we have consistently improved our methods to allow us to explore collective, dynamical patterns of happiness found in massive text corpora including Twitter, song lyrics, works of literature, movies, political speeches, and news sources. I will also discuss our work on building the Panometer, an instrument that uses social media to quantify population rates of a wide array of human behaviour such as wealth, exercise levels, obesity rates, and sleep insufficiency. Finally, I will present evidence for how 10 diverse natural languages appear to contain a striking frequency-independent positive bias, describing how this phenomenon plays a key role in our instrument's performance, and how it more deeply reflects human nature.
Peter Sheridan Dodds, Professor, University of Vermont, Director of the Vermont Complex Systems Center