The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Measuring Large-Scale Social Networks with High Resolution
Open accessAbstract
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.
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Cites
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Cited by
Modern temporal network theory: a colloquium
Holme, P. (2015) · The European Physical Journal B · doi:10.1140/epjb/e2015-60657-4 · Cited by 734
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Self-citationMobile social media usage and academic performance
Giunchiglia, F., Zeni, M., Gobbi, E., Bignotti, E., & Bison, I. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2017.12.041 · Cited by 295
Daily Stress Recognition from Mobile Phone Data, Weather Conditions and Individual Traits
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Evolving perspectives on the sources of the frequency-following response
Coffey, E. B. J., Nicol, T., White-Schwoch, T., Chandrasekaran, B., Krizman, J., Skoe, E., Zatorre, R. J., & Kraus, N. (2019) · Nature Communications · doi:10.1038/s41467-019-13003-w · Cited by 207
Metadata
- Authors
- Stopczynski, A., Sekara, V., Sapiezynski, P., Cuttone, A., Madsen, M. M., Larsen, J. E., & Lehmann, S.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2014-04-25
- Volume
- 9
- Issue
- 4
- Pages
- e95978
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W1987835826
- Cited by
- 409
- References
- 33
- FWCI
- 72.96
- Type
- journal article
- Language
- en
- Open access
- gold
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- Stopczynski, A., Sekara, V., Sapiezynski, P., Cuttone, A., Madsen, M. M., Larsen, J. E., & Lehmann, S. (2014). Measuring Large-Scale Social Networks with High Resolution. PLoS ONE. https://doi.org/10.1371/journal.pone.0095978
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.