Measuring large-scale social networks with high resolution.
This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years-the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics) for a densely connected population of 1000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. We document the participant privacy procedures and their underlying principles. The paper is concluded with early results from data analysis, illustrating the importance of multi-channel high-resolution approach to data collection.
DTU Compute, Technical University of Denmark, Kgs. Lyngby, Denmark.
Arkadiusz
A
Stopczynski
DTU Compute, Technical University of Denmark, Kgs. Lyngby, Denmark.
Vedran
V
Sekara
DTU Compute, Technical University of Denmark, Kgs. Lyngby, Denmark.
Piotr
P
Sapiezynski
DTU Compute, Technical University of Denmark, Kgs. Lyngby, Denmark.
Andrea
A
Cuttone
Department of Anthropology, University of Copenhagen, Copenhagen, Denmark.
Mette My
MM
Madsen
DTU Compute, Technical University of Denmark, Kgs. Lyngby, Denmark.
Jakob Eg
JE
Larsen
DTU Compute, Technical University of Denmark, Kgs. Lyngby, Denmark; The Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark.
Sune
S
Lehmann
D040421:Cell Phone / Q000706:statistics & numerical data; D003625:Data Collection / Q000379:methods; D003718:Denmark; D006801:Humans; D008137:Longitudinal Studies; D008962:Models, Theoretical; D060756:Social Networking; D012944:Social Support