Wikipedia growth (en)

This is the hyperlink network of the English Wikipedia with edge arrival times.

Metadata

CodeWP
Internal namewikipedia-growth
NameWikipedia growth (en)
Data sourcehttp://socialnetworks.mpi-sws.org/data-wosn2008.html
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Category
Hyperlink network
Dataset timestamp 2001 ⋯ 2008
Node meaningArticle
Edge meaningHyperlink
Network formatUnipartite, directed
Edge typeUnweighted, no multiple edges
Temporal data Edges are annotated with timestamps
ReciprocalContains reciprocal edges
Directed cyclesContains directed cycles
LoopsDoes not contain loops

Statistics

Size n =1,870,709
Volume m =39,953,145
Loop count l =0
Wedge count s =122,966,873,340
Claw count z =3,206,375,666,919,400
Cross count x =1.291 74 × 1020
Triangle count t =126,619,350
Maximum degree dmax =226,577
Maximum outdegree d+max =6,975
Maximum indegree dmax =225,883
Average degree d =42.714 4
Fill p =1.141 67 × 10−5
Size of LCC N =1,870,521
Size of LSCC Ns =1,629,321
Relative size of LSCC Nrs =0.870 964
Diameter δ =10
50-Percentile effective diameter δ0.5 =2.832 44
90-Percentile effective diameter δ0.9 =3.880 25
Mean distance δm =3.422 95
Gini coefficient G =0.683 700
Balanced inequality ratio P =0.244 004
Outdegree balanced inequality ratio P+ =0.281 987
Indegree balanced inequality ratio P =0.171 897
Relative edge distribution entropy Her =0.901 960
Power law exponent γ =1.370 51
Degree assortativity ρ =−0.041 837 0
Degree assortativity p-value pρ =0.000 00
Clustering coefficient c =0.003 089 11
Directed clustering coefficient c± =0.026 540 2
Spectral norm α =848.572
Operator 2-norm ν =690.274
Cyclic eigenvalue π =216.703
Reciprocity y =0.171 231
Non-bipartivity bA =0.240 561
Normalized non-bipartivity bN =0.021 029 4
Spectral bipartite frustration bK =0.000 256 124

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 normalized adjacency matrix

Degree assortativity

Hop distribution

In/outdegree scatter plot

Clustering coefficient distribution

Temporal distribution

Diameter/density evolution

Inter-event distribution

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] Alan Mislove. Online Social Networks: Measurement, Analysis, and Applications to Distributed Information Systems. PhD thesis, Rice Univ., 2009.