Now, scientists are discovering that a world buzzing with cell phone calls and text messages has a side benefit: reams of data about who calls whom and about where they are at what time.
Researchers are beginning to use that information to answer questions about how people behave, where they travel, and the social networks that connect them.
“There’s a ton of research in this area that’s percolating,” says David Lazer, a professor of public policy at Harvard University who studies social networks. “The hope is that these mobile phone data can offer some picture of the structure of our society. We’ve seen some beginning hints of it, the question is as we get richer data sets what additional insights we can produce.”
One of the first insights has come from the work of physicist Albert-Laszlo Barabasi and his colleagues at Northeastern University’s Center for Complex Network Research. Barabasi is an expert on networks who has discovered some of the basic laws shared by social, biological and other networks. Now, he is interested in learning more about people’s patterns of movement in their daily lives.
He analyzed six months of anonymous cell phone records from more than 100,000 people in a European country, obtained from a European cell phone provider. Those cell phone records gave an approximation of each person’s location at the time of each call, because cell phone calls are routed through the nearest cell tower.
He and his colleagues found that people tend not to stray far — almost three quarters of the people stayed mainly within about a 20-mile circle for the entire six months, and nearly half the people rarely strayed outside a six-mile circle. They also tended to go back and forth regularly between only a few locations, such as home and work.
Those results might not seem surprising, but the researchers say that the model of human motion they developed could be useful for urban planners, evacuation planning and disease tracking.
For example, during the recent swine flu outbreak, researcher Alessandro Vespignani was able to predict with some accuracy the number of swine flu cases in the U.S. by analyzing patterns of air travel. But those predictions can only be made on the city level.
“They can say how many will be affected in New York,” says Barabasi. “But they cannot say ‘would Queens be affected, or Harlem?’ If you had mobility data, you could take this prediction down to individual streets or neighborhoods.”
Recently, Barabasi has used his mobility model to study the possible spread of cell phone viruses, and to figure out why “smart phones” such as the iPhone or Blackberry — which are basically mini computers — haven’t yet succumbed to the computer viruses that plague personal computers.
Cell phones viruses can spread in one of two ways — through wireless Bluetooth devices, and through text messages. In order to pass via Bluetooth, a phone infected with the virus must get within about 10 meters of another Bluetooth-enabled phone with the same operating system.
Barabasi found that given human mobility patterns and the diversity of cell phone operating systems, two phones on the same operating system don’t get close enough to one another often enough to allow a virus to spread widely through the phone population. However, if things change — if more people get smart phones, or if the market consolidates and more phones begin to use the same operating system — then phone viruses will likely become a problem.
Meanwhile, in a lab across town from Barabasi, MIT professor Carlo Ratti is analyzing cell phone data patterns for a slightly different purpose — he aims to understand patterns of activity at the city scale rather than the individual.
In projects in Graz, Austria, Rome and Copenhagen, he and his colleagues have partnered with local telecommunications companies to map in real time the shifting patterns of cell phone use throughout the city. In Rome, they combined that information with GPS data from city public transportation to capture an ever-changing picture of the city’s activity, from traffic jams to nightlife hotspots.
The information, Ratti says, could be useful to traffic planners, emergency planners and others.
“Something like [Hurricane] Katrina would never have happened if you had such a system,” he told Technology review magazine. “You could identify where people were after a disaster (if their cell phones were working) and actually go and help them.”
Ratti’s work looks only at aggregate cell phone activity. But other studies that collect information on individual phone users — such as Barabasi’s human mobility study — raise privacy questions.
When that study was first published last year, bioethicist Arthur Caplan told the New York Times “There is plenty going on here that sets off ethical alarm bells about privacy and trustworthiness. But Barabasi told the paper that he spent “nearly half his time” on the study dealing with privacy issues, and that all of the data was anonymized.
David Lazer, of Harvard University, acknowledges the privacy risks and says that studies that use sensitive data should have strict controls — and that perhaps the data could be stored in central, secure sites like university repositories.
“In the long run, we have to think about what should be acceptable, what is now allowable, and how what is allowable should be controlled,” he says. “There are definite risks to the disclosure of sensitive data. But on the other hand there’s considerable potential for producing insight into human behavior that has real value for society.”