Wikipedia edits (cv)

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


Internal nameedit-cvwiki
NameWikipedia edits (cv)
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 =70,003
Left size n1 =2,266
Right size n2 =67,737
Volume m =591,878
Unique edge count m̿ =286,430
Wedge count s =1,548,103,349
Claw count z =11,229,432,951,521
Cross count x =74,503,298,214,840,912
Square count q =1,886,481,972
4-Tour count T4 =21,284,867,252
Maximum degree dmax =63,318
Maximum left degree d1max =63,318
Maximum right degree d2max =1,370
Average degree d =16.910 1
Average left degree d1 =261.199
Average right degree d2 =8.737 88
Fill p =0.001 866 09
Average edge multiplicity m̃ =2.066 40
Size of LCC N =68,934
Diameter δ =11
50-Percentile effective diameter δ0.5 =3.132 16
90-Percentile effective diameter δ0.9 =3.903 55
Median distance δM =4
Mean distance δm =3.258 79
Gini coefficient G =0.852 606
Balanced inequality ratio P =0.135 248
Left balanced inequality ratio P1 =0.032 827 7
Right balanced inequality ratio P2 =0.204 699
Relative edge distribution entropy Her =0.713 474
Power law exponent γ =2.113 05
Tail power law exponent γt =3.361 00
Tail power law exponent with p γ3 =3.361 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.691 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =8.911 00
Right p-value p2 =0.081 000 0
Degree assortativity ρ =−0.469 400
Degree assortativity p-value pρ =0.000 00
Spectral norm α =1,209.43
Algebraic connectivity a =0.043 564 0


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

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.