University of Washington (UW) researchers have developed a method for estimating the distribution of wealth and poverty in an area by studying metadata from calls and texts made on cellphones.
"Quantitative, rigorous measurements are key to making important decisions about social welfare allocation and the distribution of humanitarian aid, but in a lot of developing countries high-quality data doesn't exist," says UW professor Joshua Blumenstock.
The researchers found wealthier people in Rwanda tended to make more calls than poorer people, and those buying $10 worth of pre-paid phone time tend to be wealthier than those who buy 50 cents of time. In addition, those making calls during daytime business hours are systematically different from those who make irregular calls, and poorer people tend to receive more calls than they make because in Rwanda the caller pays for the call.
"We use supervised machine-learning algorithms to sort through thousands of patterns to figure out what is most correlated with wealth and poverty," Blumenstock says.
The phone metadata was overlaid onto area maps to create a visual representation of the geographic distribution of wealth.
"We are hopeful that this broad approach to detecting signals means that the methodology would work even on different call networks from different countries," says UW graduate student Gabriel Cadamuro.
From University of Washington News and Information
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