Interaction data from the Copenhagen Networks Study

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Interaction data from the Copenhagen Networks Study. / Sapiezynski, Piotr; Stopczynski, Arkadiusz; Lassen, David Dreyer; Lehmann, Sune.

In: Scientific Data, Vol. 6, 315, 11.12.2019.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Sapiezynski, P, Stopczynski, A, Lassen, DD & Lehmann, S 2019, 'Interaction data from the Copenhagen Networks Study', Scientific Data, vol. 6, 315. https://doi.org/10.1038/s41597-019-0325-x

APA

Sapiezynski, P., Stopczynski, A., Lassen, D. D., & Lehmann, S. (2019). Interaction data from the Copenhagen Networks Study. Scientific Data, 6, [315]. https://doi.org/10.1038/s41597-019-0325-x

Vancouver

Sapiezynski P, Stopczynski A, Lassen DD, Lehmann S. Interaction data from the Copenhagen Networks Study. Scientific Data. 2019 Dec 11;6. 315. https://doi.org/10.1038/s41597-019-0325-x

Author

Sapiezynski, Piotr ; Stopczynski, Arkadiusz ; Lassen, David Dreyer ; Lehmann, Sune. / Interaction data from the Copenhagen Networks Study. In: Scientific Data. 2019 ; Vol. 6.

Bibtex

@article{dd993e54072c4656bbd9af4f60fcc9f7,
title = "Interaction data from the Copenhagen Networks Study",
abstract = "We describe the multi-layer temporal network which connects a population of more than 700 university students over a period of four weeks. The dataset was collected via smartphones as part of the Copenhagen Networks Study. We include the network of physical proximity among the participants (estimated via Bluetooth signal strength), the network of phone calls (start time, duration, no content), the network of text messages (time of message, no content), and information about Facebook friendships. Thus, we provide multiple types of communication networks expressed in a single, large population with high temporal resolution, and over a period of multiple weeks, a fact which makes the dataset shared here unique. We expect that reuse of this dataset will allow researchers to make progress on the analysis and modeling of human social networks.",
author = "Piotr Sapiezynski and Arkadiusz Stopczynski and Lassen, {David Dreyer} and Sune Lehmann",
year = "2019",
month = dec,
day = "11",
doi = "10.1038/s41597-019-0325-x",
language = "English",
volume = "6",
journal = "Scientific data",
issn = "2052-4463",
publisher = "nature publishing group",

}

RIS

TY - JOUR

T1 - Interaction data from the Copenhagen Networks Study

AU - Sapiezynski, Piotr

AU - Stopczynski, Arkadiusz

AU - Lassen, David Dreyer

AU - Lehmann, Sune

PY - 2019/12/11

Y1 - 2019/12/11

N2 - We describe the multi-layer temporal network which connects a population of more than 700 university students over a period of four weeks. The dataset was collected via smartphones as part of the Copenhagen Networks Study. We include the network of physical proximity among the participants (estimated via Bluetooth signal strength), the network of phone calls (start time, duration, no content), the network of text messages (time of message, no content), and information about Facebook friendships. Thus, we provide multiple types of communication networks expressed in a single, large population with high temporal resolution, and over a period of multiple weeks, a fact which makes the dataset shared here unique. We expect that reuse of this dataset will allow researchers to make progress on the analysis and modeling of human social networks.

AB - We describe the multi-layer temporal network which connects a population of more than 700 university students over a period of four weeks. The dataset was collected via smartphones as part of the Copenhagen Networks Study. We include the network of physical proximity among the participants (estimated via Bluetooth signal strength), the network of phone calls (start time, duration, no content), the network of text messages (time of message, no content), and information about Facebook friendships. Thus, we provide multiple types of communication networks expressed in a single, large population with high temporal resolution, and over a period of multiple weeks, a fact which makes the dataset shared here unique. We expect that reuse of this dataset will allow researchers to make progress on the analysis and modeling of human social networks.

UR - http://www.scopus.com/inward/record.url?scp=85076481588&partnerID=8YFLogxK

U2 - 10.1038/s41597-019-0325-x

DO - 10.1038/s41597-019-0325-x

M3 - Journal article

C2 - 31827097

VL - 6

JO - Scientific data

JF - Scientific data

SN - 2052-4463

M1 - 315

ER -

ID: 233539083