Which was the saddest day of them all?
There are many contenders to consider surveying the wreckage of 2020 thus far. However, the Computational Story Lab of the University of Vermont, offers this answer: Sunday, May 31. That day was not only the saddest day of 2020 so far, it was also the saddest day recorded by the lab in the last 13 years. Or at least, the saddest day on Twitter.
The researchers call it the Hedonometer. It is the invention of Chris Danforth and his partner Peter Dodds, both trained mathematicians and computer scientists and the co-directors of the lab. The Hedonometer has been up and running for more than a decade, measuring word choices across millions of tweets, every day, the world over, to come up with a moving measure of well-being.
In fact, the last time the New York Times checked in with the Hedonometer team, in 2015, the main finding to emerge was our tendency toward relentless positivity on social media. "One of the happiest years on Twitter, at least for English," Danforth said with a note of rue. Since then it has been a long decline."
What has remained constant is this: "Happiness is hard to know. It's hard to measure," he said. "We don't have a lot of great data about how people are doing."
The Computational Story Lab is part of a small but growing field of researchers who try to parse our national mental health through the prism of our online life. After all, never before have we had such an incredible stockpile of real-time data — what's known as our "digital traces" — to choose from.
And never has that stockpile of information towered as high as it does now: In the first months of the pandemic, Twitter reported a 34% increase in daily average user growth. Without our normal social life as antidote and anchor, our social media now feels more like real life than ever before.
Since 2008, the Hedonometer has gathered a random 10% of all public tweets, every day, across a dozen languages. The tool then looks for words that have been ranked for their happy or sad connotation, counts them, and calculates a kind of national happiness average based on which words are dominating the discourse.