sp_hypertext — Hypertext 2009 dynamic contact network
- Description
Temporal network of face-to-face proximity contacts among about 110 attendees of the ACM Hypertext 2009 conference in Turin, Italy, over about 2.5 days (29 June to 1 July 2009). The data were collected by the SocioPatterns collaboration as part of the Live Social Semantics application: attendees volunteered to wear radio badges that detected face-to-face proximity. Nodes are attendees. No personal data or other metadata are included. The data are provided in two forms:
contacts: each edge is a contact between two attendees active during a 20-second interval of the data collection, so that a pair of attendees is connected by one edge per interval in which they were in contact.intervals: each edge is a pair of attendees that were in contact at least once, annotated with the list of time intervals during which the contact was active.
The networks have the following properties:
id: the anonymous identifier of the attendee.time(contacts): the end of the 20-second interval $[t - 20\,\text{s}, t]$ during which the contact was active, in seconds since 8:00 am of 29 June 2009 (UNIX time 1246255200).intervals(intervals): the list of time intervals[start, end]of the contact, in the same units astime.
- Tags
- Social Offline Unweighted Temporal
- Citation
-
- L. Isella et al., "What’s in a crowd? Analysis of face-to-face behavioral networks." J. Theor. Bio. 271, 166-180 (2011). arXiv:1006.1260
- Upstream URL OK
- https://sociopatterns.org/datasets/hypertext-2009-dynamic-contact-network/
- Upstream license
- Creative Commons Attribution-NonCommercial-ShareAlike, http://creativecommons.org/licenses/by-nc-sa/3.0/
- 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 contacts 113 20,818 368.46 322.99 45.63 13.09 0.32 0.55 3 1.00 Undirected Unipartite id time 36 KiB 74 KiB 66 KiB 60 KiB intervals 113 2,196 38.87 18.35 45.63 0.81 -0.12 0.50 3 1.00 Undirected Unipartite id intervals 50 KiB 73 KiB 72 KiB 54 KiB - Ridiculograms*