In 1881, the optimistic Irish economist Francis Edgeworth imagined a strange device called a "hedonimeter", in other words, a happiness sensor; 128 years later his dream came true.
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For decades, social scientists have had a devilish headache in trying to measure happiness. Surveys have revealed some useful information, but these are plagued by the unpleasant fact that people misreport and misremember their feelings when confronted by the guy with the clipboard. Ditto for studies where volunteers call in their feelings via PDA or cell phone. People get squirrely when they know they're being studied.
But what if you had a remote-sensing mechanism that could record how millions of people around the world were feeling on any particular day — without their knowing?
That's exactly what Peter Dodds and Chris Danforth, a mathematician and computer scientist working in the Advanced Computing Center at the University of Vermont, have created. "The proliferation of personal online writing such as blogs gives us the opportunity to measure emotional levels in real time," they write in their study, "Measuring the Happiness of Large-Scale Written Expression: Songs, Blogs, and Presidents,3" now available in an early online edition of the journal.
Their answer to Edgeworth's daydream begins with a website "We feel fine" that mines through some 2.3 million blogs, looking for sentences beginning with "I feel" or "I am feeling." "We gathered nearly 10 million sentences from their site," Dodds says. Then, drawing on a standardized "psychological valence" of words established by the Affective Norms for English Words (ANEW) study, each sentence receives a happiness score. In the ANEW study, a large pool of participants graded their reaction to 1,034 words, forming a kind of "happy-unhappy" scale from 1 to 9. For example, "triumphant" averaged 8.87, "paradise" 8.72, "pancakes" 6.08, "vanity" 4.30, "hostage" 2.20, and "suicide" 1.25.
The sentence "I feel lazy" would receive a score of 4.38. "Our method is only reasonable for large-scale texts, like what's available on the Web," Dodds says. "Any one sentence might not show much. There's too much variability in individual expression." But that's the beauty of big data sets and statistics. "It's like measuring the temperature. You don't care where the atoms are," Dodds says. "You want to know the temperature of this room or this town. It's a coarser scale. We're interested in the collective story."
Election Day 2008 showed a spike in the word "proud." "That was the biggest deviation in the last four years," Danforth says. "To have 'proud' be the word that moves the needle is remarkable." Interestingly, their results run contrary to recent social science data that suggest that people basically feel the same at all ages of life. Instead, Dodds and Danforth's method shows a more commonsensical result: young teenagers are unhappiest with a disproportionate use of "sick," "hate," "stupid," "sad," "depressed," "bored," "lonely," "mad," and, not surprisingly, "fat." Then people get happier until they are old, when happiness drops off. ■