# Netzschleuder network catalogue, repository and centrifuge

Problems with this dataset? Open an issue.
You may also take a look at the source code.
The networks in this dataset can be loaded directly from graph-tool with:
import graph_tool.all as gt
g = gt.collection.ns["sp_hypertext/contacts"]

(and likewise for the other networks available.)

# sp_hypertext — Hypertext 2009 dynamic contact network

Description

The temporal network of contacts among attendees of the ACM Hypertext 2009 conference, which spanned 2.5 days of time.1

This dataset was collected during the ACM Hypertext 2009 conference, where the SocioPatterns project deployed the Live Social Semantics application. Conference attendees volunteered to wear radio badges that monitored their face-to-face proximity. The dataset published here represents the dynamical network of face-to-face proximity of ~110 conference attendees over about 2.5 days. No personal data are released here, and no metadata collected by the Live Social Semantics application are exposed. We provide two data files, described below.

Contact List. This is a tab-separated list representing the active contacts during 20-second intervals of the data collection. Each line has the form “t i j“, where i and j are the anonymous IDs of the persons in contact, and the interval during which this contact was active is [ t – 20s, t ]. If multiple contacts are active in a given interval, you will see multiple lines starting with the same value of t. Time is measured in seconds since 8am on Jun 29th 2009 (UNIX ctime 1246255200).

Contact Intervals. This file is in JSON format and contains a dictionary. Each key is a person ID and the corresponding value is a dictionary of neighbors of that person in the contact network. This dictionary of neighbors has person IDs as keys and, for each key, the value gives the list of time intervals during which the corresponding contact was active. Time is measured as above.

1. Description obtained from the ICON project.

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)., http://arxiv.org/abs/1006.1260
Upstream URL OK
http://www.sociopatterns.org/datasets/hypertext-2009-dynamic-contact-network/
Networks
Tip: click on the table header to sort the list. Hover your mouse over it to obtain a legend.
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 38 KiB 81 KiB 75 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 51 KiB 74 KiB 73 KiB 54 KiB
Ridiculograms