Researchers have created a 21st century global mood ring with data mining


After your morning stock market and weather updates, maybe add a check of the hedonometer to your list. The new site draws on tweets — and soon, the New York Times, Google Trends, and other sources of textual sentiment — to gauge population-level happiness. This big data approach is taking the collective mood temperature across space and time, but it’s unlikely to reveal the secret to achieving happiness.

Launching today and updated every 24 hours with faster refresh rates to come, uses English-language tweets to create a happiness index. The system is based on a 10,000-word strong “emotional temperature” database, where words are ranked on a scale of 1-9 by volunteers using Amazon’s Mechanical Turk. Words like “laughter,” “happiness,” and “love” top the list, while “loneliness,” “bad,” “inflation,” and “surgery,” along with assorted expletives, round out the bottom, with rankings close to 1. The emoticon “:(“ has a rating of 2.36.

Users can zoom in on any day all the way back to September 10, 2008, check out the balance of positive and negative words, and see how these compare to the week before and after. Saturdays, for example, tend to be happier than Tuesdays. Christmas Day stands out as being the happiest day of the year, every year. The hedonometer developers, mathematicians from the University of Vermont along with scientists from the MITRE Corporation, found that April 15, the day of the Boston bombings, was the unhappiest day on record, with an average happiness index of 5.88. Other recent sad days include December 14 last year (Newtown school shooting) and June 25, 2009 (death of Michael Jackson).

Indeed, eyeballing the global happiness index suggests a slight downward slope since 2008. Whether or not this effect is real depends on establishing a normal background happiness level, and comparison with geographic, socioeconomic, and political metrics. What’s interesting is that the hedonometer is turning more than 50 million daily micro-statements into a “quantitative macro-story,” as UV’s Chris Danforth put it. Individually insignificant words and tweets swell into a collective emotional response, the blips and dips of which stand out and correlate with major events.


The research from Danforth and his colleagues got some press earlier this month, when they reported that happiness went up the further Twitter users were from home. Other insights from the same team included the fact that obesity and happiness were inversely correlated, and that cities’ happiness scores were related to swear words, suggesting that “geoprofanity” could be a good marker for regional happiness differences.

The hedonometer is set to draw on more data streams soon, including blogs, news transcripts, and shortened links, and will be data mining in a dozen languages. Nonetheless, the happiness index will remain an aggregate measure, like a nation’s GDP, and may not have much impact in and of itself. The underlying methodology, however, is the real driver, with broad applicability to big data, whether social media-generated or not.

Image via Chris Danforth, University of Vermont


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