Netzschleuder network catalogue, repository and centrifuge

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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["reuters"]

reuters — Reuters news stories (1987, 2000)

Description

A bipartite network of Reuters news stories and words. Edges connect each story to all the words it contains.¹

Description obtained from the ICON project. ↩

Tags

Informational Language Unweighted

Citation

D. Lewis., et al. "Rcv1: A new benchmark collection for text categorization research." J. Machine Learning Research 5, 361-397 (2004)., http://www.jmlr.org/papers/v5/lewis04a.html

Upstream URL OK

http://konect.cc/networks/reuters

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
reuters	1,065,176	60,569,726	113.73	1700.21	2298.04	3.48	-0.25	0.00	6	1.00	Undirected	Bipartite	meta	weight	103.7 MiB	283.8 MiB	226.6 MiB	230.3 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.