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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, telecommu...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4000208/ https://www.ncbi.nlm.nih.gov/pubmed/24770359 http://dx.doi.org/10.1371/journal.pone.0095978 |
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author | Stopczynski, Arkadiusz Sekara, Vedran Sapiezynski, Piotr Cuttone, Andrea Madsen, Mette My Larsen, Jakob Eg Lehmann, Sune |
author_facet | Stopczynski, Arkadiusz Sekara, Vedran Sapiezynski, Piotr Cuttone, Andrea Madsen, Mette My Larsen, Jakob Eg Lehmann, Sune |
author_sort | Stopczynski, Arkadiusz |
collection | PubMed |
description | 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 1 000 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. |
format | Online Article Text |
id | pubmed-4000208 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-40002082014-04-29 Measuring Large-Scale Social Networks with High Resolution Stopczynski, Arkadiusz Sekara, Vedran Sapiezynski, Piotr Cuttone, Andrea Madsen, Mette My Larsen, Jakob Eg Lehmann, Sune PLoS One Research Article 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 1 000 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. Public Library of Science 2014-04-25 /pmc/articles/PMC4000208/ /pubmed/24770359 http://dx.doi.org/10.1371/journal.pone.0095978 Text en © 2014 Stopczynski et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Stopczynski, Arkadiusz Sekara, Vedran Sapiezynski, Piotr Cuttone, Andrea Madsen, Mette My Larsen, Jakob Eg Lehmann, Sune Measuring Large-Scale Social Networks with High Resolution |
title | Measuring Large-Scale Social Networks with High Resolution |
title_full | Measuring Large-Scale Social Networks with High Resolution |
title_fullStr | Measuring Large-Scale Social Networks with High Resolution |
title_full_unstemmed | Measuring Large-Scale Social Networks with High Resolution |
title_short | Measuring Large-Scale Social Networks with High Resolution |
title_sort | measuring large-scale social networks with high resolution |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4000208/ https://www.ncbi.nlm.nih.gov/pubmed/24770359 http://dx.doi.org/10.1371/journal.pone.0095978 |
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