Wikipedia edits (udm)

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


Internal nameedit-udmwiki
NameWikipedia edits (udm)
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 =11,065
Left size n1 =1,027
Right size n2 =10,038
Volume m =96,529
Unique edge count m̿ =46,685
Wedge count s =33,041,094
Claw count z =28,568,102,865
Cross count x =22,975,137,170,795
Square count q =51,174,040
4-Tour count T4 =541,686,958
Maximum degree dmax =10,228
Maximum left degree d1max =10,228
Maximum right degree d2max =284
Average degree d =17.447 6
Average left degree d1 =93.991 2
Average right degree d2 =9.616 36
Fill p =0.004 528 56
Average edge multiplicity m̃ =2.067 67
Size of LCC N =10,581
Diameter δ =12
50-Percentile effective diameter δ0.5 =3.323 21
90-Percentile effective diameter δ0.9 =4.816 51
Median distance δM =4
Mean distance δm =3.646 77
Gini coefficient G =0.845 388
Balanced inequality ratio P =0.158 217
Left balanced inequality ratio P1 =0.062 644 4
Right balanced inequality ratio P2 =0.210 704
Relative edge distribution entropy Her =0.761 521
Power law exponent γ =2.126 15
Tail power law exponent γt =1.741 00
Tail power law exponent with p γ3 =1.741 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.461 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =3.681 00
Right p-value p2 =0.024 000 0
Degree assortativity ρ =−0.291 938
Degree assortativity p-value pρ =0.000 00
Spectral norm α =476.363
Algebraic connectivity a =0.026 190 0
Spectral separation 1[A] / λ2[A]| =1.903 63
Controllability C =9,136
Relative controllability Cr =0.827 686


Fruchterman–Reingold graph drawing

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

Double Laplacian graph drawing

Delaunay graph drawing

Edge weight/multiplicity distribution

Temporal distribution

Temporal hop 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.