Researchers tap phone data to establish mobility patterns

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Researchers tap phone data to establish mobility patterns

Big data finds human behaviour predictable.

A group of international scientists have used mobile phone data to work out a set of standard human mobility patterns, which they argue could be used for urban planning and business analytics.

In a paper published today in The Royal Society journal Interface, the researchers, led by MIT’s Christian Schneider, argue the digital footprint left by mobile phone activity could be used to help substitute travel surveys.

The researchers used a survey and mobile phone billing data from Paris, and a survey from Chicago, which enabled them to reproduce the entire daily activity patterns of the anonymous individuals.

The phone billing data provided information about incoming and outgoing calls and SMS, including locations of the operating towers, time of events and user identification numbers.

“Advances in transforming large data into meaningful information are essential to improve our understanding of sociotechnical systems,” the researchers write in the paper.

“In our study we contribute to this end by analysing networks of daily trips obtained from individual’s surveys and anonymised mobile phone data.

“We found that both travel surveys and phone traces from two different cities reveal the same set of ubiquitous networks that we call motifs.”

The researchers say these motifs, which equate to just 17 unique networks, could be used to model and simulate urban activity.

The research revealed 90 percent of the population visits less than seven locations on a daily basis, despite the difference between the cities studied.

The researchers have published C++ code of their proposed model, the algorithms to identify motifs and simulated data to test all algorithms here.

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