There’s a new study out in tomorrow’s Science magazine that’s generating lots of buzz — trending, if you will — this afternoon: researchers have mined two years’ worth of Twitter data, from over 2.4 million users, to study the daily, weekly, and seasonal variations in the mood of people from 84 countries around the world.

As one journalist put it:

But while the findings aren’t necessarily surprising — and this isn’t the first “Twitter study” either — the fact that the two social scientists mined such a large data set to solve a problem that’s usually reserved for surveys or individual diaries is noteworthy.

As the news staff of Science magazine points out in describing the article:

Making sense of the deluge of data from Twitter and other social media will require researchers to employ an interdisciplinary skill set that draws from traditional social sciences, statistics, and computer science… Although some traditionally trained social scientists remain skeptical about whether anything “serious” can be learned from social media and question whether those who use it are representative of the population as a whole, others insist the rewards could be rich.

 

“There was this intriguing paradox where for most of the 20th century we seemed to know more about exploding stars at the edge of the galaxy and the proteome of yeast than we knew about how large human social groups function,” says Jon Kleinberg, a computer scientist at Cornell. But the digital detritus of 21st century life online may change all that, Kleinberg says: “Interesting things happen when you can take what was once invisible and make it visible.”

Indeed, the study is an example of the many questions and problems that we will be able to address as we develop novel, interdisciplinary approaches to make sense of the unprecedented amounts of data being generated — through social media, in healthcare, in education, in the basic sciences, and so on.

(Contributed by Erwin Gianchandani, CCC Director)