Netzschleuder network catalogue, repository and centrifuge

Problems with this dataset? Open an issue.
You may also take a look at the source code.

The network in this dataset can be loaded directly from graph-tool with:
import graph_tool.all as gt
g = gt.collection.ns["visualizeus"]

visualizeus — vi.sualize.us picture tagging network

Description

Three bipartite networks of tag-picture, user-picture, and user-tag linkages that represent the folksonomy of the picture tagging network of vi.sualize.us. The date of this snapshot is uncertain.¹

Description obtained from the ICON project. ↩

Tags

Informational Folksonomy Unweighted Multigraph

Citation

N. Neubauer and K. Obermayer. "Analysis of the Visualize.us folksonomy." Unpublished (2010), https://networks.skewed.de/net/visualizeus

Upstream URL OK

http://konect.cc/networks/pics_ti

Networks

Tip: hover your mouse over a table header 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
visualizeus	577,437	2,298,816	7.96	559.95	279.27	341.29	-0.12	0.00	17	0.98	Undirected	Bipartite			12.6 MiB	20.1 MiB	19.6 MiB	16.5 MiB

Ridiculograms^*

^* These are automatically generated force-directed visualizations, and can be quite meaningless for networks both big and small. They should not be taken seriously as sources of scientific insight. See here for a discussion.