Communications of the ACM
Mobile Data Show Friend Networks
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A study published in Proceedings of the National Academy of Sciences shows that friendships can be inferred with 95% accuracy by studying cellphone call records and the proximity of users. "We gave out a set of phones that were installed with a piece of 'uber-spyware,' " says the study's lead author Nathan Eagle, now at the Santa Fe Institute. "It's invisible to the user but logs everything: communication, users' locations, people's proximity by doing continuous Bluetooth scans."
Researchers equipped 94 mobile phones in the U.S. with logging software to collect call data. The results show that those with friends near their work were happier, while those who called friends while at work were less satisfied, which conflicts with the answers reported by the users themselves during surveys.
"What we found was that people's responses were wildly inaccurate," Eagle says. "For people who said that a given individual was a friend, they dramatically overestimated the amount of time they spent. But for people who were not friends, they dramatically underestimated that amount of time."
The researchers are conducting a study on a larger group of 1,000 people in Helsinki, Finland. They also are engaged in an ongoing trial of the approach in Kenya, which Eagle says includes participants ranging from computer science students to people who have never had a phone before. Eagle says this type of research can go beyond mapping phone users' friend networks and could help a variety of research efforts, including modeling the spread of disease and the design of urban spaces.
From BBC News
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