Wikispeedia

These are paths from the Wikispeedia game, in which users are tasked to find a article of the English Wikipedia, starting from a given article of the English Wikipedia, being allowed to only click links. Nodes are articles of the English Wikipedia, and edges represent clicks.

Metadata

CodeWS
Internal namewikispeedia
NameWikispeedia
Data sourcehttp://snap.stanford.edu/data/wikispeedia.html
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Category
Hyperlink network
Node meaningArticle
Edge meaningClick
Network formatUnipartite, directed
Edge typeUnweighted, multiple edges
ReciprocalContains reciprocal edges
Directed cyclesContains directed cycles
LoopsDoes not contain loops
Paths The edges form paths

Statistics

Size n =4,179
Volume m =343,950
Unique edge count m̿ =57,572
Wedge count s =5,350,052
Claw count z =1,231,596,321
Cross count x =314,843,715,024
Triangle count t =119,886
Square count q =4,843,415
4-Tour count T4 =60,248,528
Maximum degree dmax =23,348
Maximum outdegree d+max =11,557
Maximum indegree dmax =11,791
Average degree d =164.609
Fill p =0.003 297 39
Average edge multiplicity m̃ =5.974 26
Size of LCC N =4,179
Size of LSCC Ns =3,766
Relative size of LSCC Nrs =0.901 173
Diameter δ =5
50-Percentile effective diameter δ0.5 =2.346 75
90-Percentile effective diameter δ0.9 =2.927 82
Median distance δM =3
Mean distance δm =2.784 22
Gini coefficient G =0.747 283
Relative edge distribution entropy Her =0.919 506
Power law exponent γ =1.382 01
Tail power law exponent γt =2.571 00
Degree assortativity ρ =−0.115 584
Degree assortativity p-value pρ =0.000 00
In/outdegree correlation ρ± =+0.899 184
Clustering coefficient c =0.067 225 1
Spectral norm α =2,742.02
Operator 2-norm ν =1,474.05
Cyclic eigenvalue π =1,275.36
Algebraic connectivity a =0.716 505
Reciprocity y =0.245 675

Plots

Degree distribution

Cumulative degree distribution

Lorenz curve

Spectral distribution of the adjacency matrix

Spectral distribution of the normalized adjacency matrix

Spectral distribution of the Laplacian

Spectral graph drawing based on the adjacency matrix

Spectral graph drawing based on the Laplacian

Spectral graph drawing based on the normalized adjacency matrix

Degree assortativity

Zipf plot

Hop distribution

Delaunay graph drawing

In/outdegree scatter plot

Edge weight/multiplicity distribution

Clustering coefficient distribution

Average neighbor degree distribution

SynGraphy

Matrix decompositions plots

Downloads

References

[1] Jérôme Kunegis. KONECT – The Koblenz Network Collection. In Proc. Int. Conf. on World Wide Web Companion, pages 1343–1350, 2013. [ http ]
[2] Jure Leskovec. Stanford Network Analysis Project. http://snap.stanford.edu/, September 2014.