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- W2169760170 abstract "Introduction As citizens of the information age, we are leaving pervasive digital traces of our idiosyncratic behavior– in emails, on online social networking sites, in mobile phone call logs, in ATM machines, in metropolitan train systems. Researchers in the emerging field of Computational Social Science (CSS) are attempting to create quantitative models of large-scale human social systems from these digital traces, as well as address key questions like privacy, data-ownership and sharing of interaction data. Recent work has focused on online techniques, e.g. mining corporate emails and crawling social networking sites to build maps of social interactions. In contrast, mass-market mobile phones allow sensing and analysis of the building blocks of social interactions – those that occur face-to-face. Eagle & Pentland (2005) and later Dong & Pentland (2006) used Bluetooth proximity information to recognize social patterns in daily activity infer relationships, identify socially relevant locations and model organizational rhythms." @default.
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- W2169760170 date "2007-01-01" @default.
- W2169760170 modified "2023-09-27" @default.
- W2169760170 title "Mob.Media: A Mobile Phone Platform for Computational Social Science" @default.
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