Wikipedia edits (jv)

This is the bipartite edit network of the Javanese Wikipedia. It contains users and pages from the Javanese Wikipedia, connected by edit events. Each edge represents an edit. The dataset includes the timestamp of each edit.


Internal nameedit-jvwiki
NameWikipedia edits (jv)
Data source
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Authorship network
Dataset timestamp 2017-10-20
Node meaningUser, article
Edge meaningEdit
Network formatBipartite, undirected
Edge typeUnweighted, multiple edges
Temporal data Edges are annotated with timestamps


Size n =135,468
Left size n1 =3,899
Right size n2 =131,569
Volume m =1,151,435
Unique edge count m̿ =594,579
Wedge count s =5,286,577,222
Claw count z =61,214,537,844,755
Cross count x =660,387,750,334,854,784
Square count q =5,522,934,618
4-Tour count T4 =65,331,114,126
Maximum degree dmax =128,853
Maximum left degree d1max =128,853
Maximum right degree d2max =1,037
Average degree d =16.999 4
Average left degree d1 =295.315
Average right degree d2 =8.751 57
Fill p =0.001 159 05
Average edge multiplicity m̃ =1.936 56
Size of LCC N =133,977
Diameter δ =10
50-Percentile effective diameter δ0.5 =3.206 93
90-Percentile effective diameter δ0.9 =5.134 90
Median distance δM =4
Mean distance δm =3.477 70
Gini coefficient G =0.827 113
Balanced inequality ratio P =0.167 035
Left balanced inequality ratio P1 =0.034 979 0
Right balanced inequality ratio P2 =0.237 067
Relative edge distribution entropy Her =0.715 601
Power law exponent γ =2.065 37
Tail power law exponent with p γ3 =3.141 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.671 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =7.441 00
Right p-value p2 =0.051 000 0
Degree assortativity ρ =−0.321 518
Degree assortativity p-value pρ =0.000 00
Spectral norm α =1,209.50


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

Edge weight/multiplicity distribution

Temporal distribution

Diameter/density evolution

Matrix decompositions plots



[1] Jérôme Kunegis. KONECT – The Koblenz Network Collection. In Proc. Int. Conf. on World Wide Web Companion, pages 1343–1350, 2013. [ http ]
[2] Wikimedia Foundation. Wikimedia downloads., January 2010.