It’s hard to appreciate just how quickly and thoroughly Twitter has taken over the world. Just seven years ago, in 2006, it was an idea sketched out on a pad of paper. Now, the service is used by an estimated 554 million users—a number that amounts to nearly 8 percent of the all humans on the planet—and an estimated 170 billion tweets have been sent, with that number climbing by roughly 58 million every single day.
All these tweets provide an invaluable source of news, entertainment, conversation and connection between people. But for scientists, they’re also valuable as something rather different: raw data.
Because Twitter features an open API (which allows for tweets to be downloaded as raw, analyzable data) and many tweets are geotagged, researchers can use billions of these tweets and analyze them by location to learn more about the geography of humans across the planet. Last fall, as part of the Global Twitter Heartbeat, a University of Illinois team analyzed the language and location of over a billion tweets from across the U.S. to create sophisticated maps of things like positive and negative emotions expressed during Hurricane Sandy, or support for Barack Obama or Mitt Romney during the Presidential election.
As Joshua Keating noted on Foreign Policy‘s War of Ideas blog, members of the same group, led by Kalev Leetaru, have recently gone one step further. As published in a new study earlier this week in the online journal First Monday, they analyzed the locations and languages of 46,672,798 tweets posted between October 23 and November 30 of last year to create a stunning portrait of human activity around the planet, shown at the top of the post. They made use of the Twitter decahose, a data stream that captures a random 10 percent of all tweets worldwide at any given time (which totaled 1,535,929,521 for the time period), and simply focused on the tweets with associated geographic data.
As the researchers note, the geographic density of tweets in many regions—especially in the Western world, where computers, mobile devices, and Twitter are all used at peak levels—closely matches rates of electrification and lighting use. As a result, the maps of tweets end up looking a lot like satellite images of artificial light at night.
Click here to see Maps
Found both the article and maps very interesting.
What did you think?