For nine months, Eagle's team recorded data from the phones of 94 students and staff at MIT. By using blue-tooth technology and phone masts, they could monitor the movements of the participants, as well as their phone calls. Their main goal with this preliminary study was to compare data collected from the phones with subjective self-report data collected through traditional survey methodology.
The participants were asked to estimate their average spatial proximity to the other participants, whether they were close friends, and to indicate how satisfied they were at work.
Some intriguing findings emerged. For example, the researchers could predict with around 95 per cent accuracy who was friends with whom by looking at how much time participants spent with each other during key periods, such as Saturday nights.
There were also discrepancies between the two data sets. For example, participants tended to overestimate how much time they spent with friends, and underestimate how much time they spent with non-friends. Also, the accuracy of the self-report proximity data tended to peak over the previous seven days (at which point it correlated highly with the phone records), but then its accuracy tailed off. This provides useful information about the validity of survey records over time, and an interesting insight into people's memories for their social interactions.
As regards satisfaction at work, it turned out that people who were in closer proximity to their friends during work time, tended to be happier at work, whilst participants less happy at work tended to make more phone calls to friends during work hours.
"Data collected from mobile phones have the potential to provide insight into the underlying relational dynamics of organisations, communities and potentially societies," the researchers said.
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Eagle, N., Pentland, A., & Lazer, D. (2009). Inferring friendship network structure by using mobile phone data. Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.0900282106
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