2010 · 280 citations · 8 references
Open access
ComputingInformation TechnologyData MiningMobile ComputingMobile SystemsMobile Human-computer InteractionMobile SensingParticipatory Data CollectionHuman Mobility PatternsLarge-scale Data ProcessingMobile Data CollectionMobile Device Location DataMobile Spatial Data CollectionMobile Usage
Abstract—Mobile phones have recently been used to collect large-scale continuous data about human behavior. In a paradigm known as people centric sensing, users are not only the carriers of sensing devices, but also the sources and consumers of sensed events. This paper describes a data collection campaign wherein Nokia N95 phones are allocated to a heterogeneous sample of nearly 170 participants from Lausanne, a mid-tier city in Switzerland, to be used over a period of one year. The data collection software runs on the background of the phones in a non-intrusive manner, yielding data on modalities such as social interaction and spatial behavior. The main motivations for organizing a new campaign on top of the ones that have been successfully conducted in the past are the following: First, in comparison to the Reality Mining data, generated in 2004-2005, the present data set is expected to provide a richer means to study location attributes, in particular, because today’s mobile phones are more powerful and equipped with more sensors. Second, we aim to recruit a heterogeneous set of participants, comprising family and leisure related social networks in addition to organizationally driven ones. This paper provides a methodological description of the project and shows the potential of the resulting data set in terms of illuminating multiple aspects of human behavior. I.
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David Lazer, Alex Pentland, Lada A. Adamic et al. · Science · 2009 · 3.3K citations · Full text
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