Wikinews edits (ru)

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


Internal nameedit-ruwikinews
NameWikinews edits (ru)
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 =118,212
Left size n1 =2,041
Right size n2 =116,171
Volume m =491,861
Unique edge count m̿ =169,412
Wedge count s =2,058,248,683
Claw count z =29,318,727,310,510
Cross count x =346,665,545,712,441,408
Square count q =32,919,706
4-Tour count T4 =8,496,895,160
Maximum degree dmax =196,122
Maximum left degree d1max =196,122
Maximum right degree d2max =41,912
Average degree d =8.321 68
Average left degree d1 =240.990
Average right degree d2 =4.233 94
Fill p =0.000 714 502
Average edge multiplicity m̃ =2.903 34
Size of LCC N =117,410
Diameter δ =11
50-Percentile effective diameter δ0.5 =3.238 67
90-Percentile effective diameter δ0.9 =3.902 84
Median distance δM =4
Mean distance δm =3.357 31
Gini coefficient G =0.860 869
Balanced inequality ratio P =0.128 201
Left balanced inequality ratio P1 =0.034 566 7
Right balanced inequality ratio P2 =0.199 721
Relative edge distribution entropy Her =0.678 471
Power law exponent γ =5.406 69
Tail power law exponent γt =2.701 00
Tail power law exponent with p γ3 =2.701 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.701 00
Left p-value p1 =0.354 000
Right tail power law exponent with p γ3,2 =2.761 00
Right p-value p2 =0.000 00
Degree assortativity ρ =−0.212 529
Degree assortativity p-value pρ =0.000 00
Spectral norm α =60,247.8
Algebraic connectivity a =0.042 932 4


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.