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Thursday, February 21, 2008

Reality Mining 

The good applications are in epidemiology and personal health care. The bad applications -- well, you can certainly guess the bad applications without any help from us:
Every time you use your cell phone, you leave behind a few bits of information. The phone pings the nearest cell-phone towers, revealing its location. Your service provider records the duration of your call and the number dialed.

Some people are nervous about trailing digital bread crumbs behind them. Sandy ­Pentland, however, revels in it. In fact, the MIT professor of media arts and sciences would like to see phones collect even more information about their users, recording everything from their physical activity to their conversational cadences. With the aid of some algorithms, he posits, that information could help us identify things to do or new people to meet . . . .

Within the next few years, Pentland predicts, reality mining will become more common, thanks in part to the proliferation and increasing sophistication of cell phones. Many handheld devices now have the processing power of low-end desktop computers, and they can also collect more varied data, thanks to devices such as GPS chips that track location. And researchers such as Pentland are getting better at making sense of all that information.

To create an accurate model of a person's social network, for example, Pentland's team combines a phone's call logs with information about its proximity to other people's devices, which is continuously collected by Bluetooth sensors. With the help of factor analysis, a statistical technique commonly used in the social sciences to explain correlations among multiple variables, the team identifies patterns in the data and translates them into maps of social relationships. Such maps could be used, for instance, to accurately categorize the people in your address book as friends, family members, acquaintances, or coworkers. In turn, this information could be used to automatically establish privacy settings--for instance, allowing only your family to view your schedule. With location data added in, the phone could predict when you would be near someone in your network. In a paper published last May, ­Pentland and his group showed that cell-phone data enabled them to accurately model the social networks of about 100 MIT students and professors. They could also precisely predict where subjects would meet with members of their networks on any given day of the week.
More on our favorite mod con here and here.

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