copenhagen — Copenhagen Networks Study
- Description
Networks of interactions among about 700 university students at the Technical University of Denmark, from the Copenhagen Networks Study. Participants were given smartphones that recorded physical proximity to other participants (via Bluetooth), phone calls and text messages; their Facebook friendships were also collected. The data released by P. Sapiezynski and collaborators cover a period of four weeks, during which Bluetooth scans were performed every five minutes. There are four networks, all on participants of the study:
sms: an edge from the sender to the recipient of each text message, with itstimestamp.calls: an edge from the caller to the recipient of each phone call, with itstimestampanddurationin seconds (-1 for a missed call).bt: an undirected edge for each Bluetooth scan in which two participants' phones detected each other, with itstimestampandrssi, the received signal strength indicator (in dBm, a proxy for physical proximity). Scans that detected no participant, or only devices outside the study, are not included.fb_friends: an undirected edge for each Facebook friendship between participants that existed throughout the observation period.
Timestamps are in seconds since the beginning of the observation period.
The networks have the following properties:
- Nodes:
id, the participant's identifier in the original data, shared across the four networks;female, the participant's gender: 1 for female, 0 otherwise, and -1 where unknown. - Edges:
timestamp,durationandrssi, as described above.
- Tags
- Social Offline Unweighted Weighted Timestamps Multilayer Metadata
- Citation
-
- P. Sapiezynski, et al., "Interaction data from the Copenhagen Networks Study." Scientific Data 6, 315 (2019) 10.1038/s41597-019-0325-x Sci-Hub
- Upstream URL 403
- https://doi.org/10.6084/m9.figshare.7267433
- Networks
-
Tip: click on a column header to sort the list, or hover over it for a description.
Column legend
- $\left<k\right>$
- Mean degree
- $\sigma_k$
- Standard deviation of the degrees
- $\lambda_h$
- Largest eigenvalue of the Hashimoto (non-backtracking) matrix
- $\tau$
- Random walk mixing time
- $r$
- Degree assortativity
- $c$
- Global clustering coefficient
- $\oslash$
- (Pseudo-) diameter
- $S$
- Relative size of the largest component
- NPs
- Node properties
- EPs
- Edge properties
Name Nodes Edges $\left<k\right>$ $\sigma_k$ $\lambda_h$ $\tau$ $r$ $c$ $\oslash$ $S$ Kind Mode NPs EPs gt GraphML GML csv sms 568 24,333 42.84 247.58 3.47 1653.09 0.87 0.03 20 0.80 Directed Unipartite id female timestamp 84 KiB 119 KiB 115 KiB 110 KiB fb_friends 800 6,429 16.07 13.38 30.19 8.18 0.18 0.24 7 1.00 Undirected Unipartite id female 24 KiB 36 KiB 36 KiB 32 KiB calls 536 3,600 6.72 18.28 4.14 452.76 0.66 0.09 22 0.65 Directed Unipartite id female timestamp duration 28 KiB 40 KiB 39 KiB 33 KiB bt 692 2,426,279 7012.37 4950.73 281.14 17.83 0.14 0.71 5 1.00 Undirected Unipartite id female timestamp rssi 3.2 MiB 10.3 MiB 9.6 MiB 9.1 MiB - Ridiculograms*