Wikipedia edits (mdf)

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


Internal nameedit-mdfwiki
NameWikipedia edits (mdf)
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 =5,216
Left size n1 =643
Right size n2 =4,573
Volume m =46,607
Unique edge count m̿ =22,016
Wedge count s =6,176,912
Claw count z =1,882,042,198
Cross count x =526,796,360,578
Square count q =11,093,090
4-Tour count T4 =113,524,384
Maximum degree dmax =3,890
Maximum left degree d1max =3,890
Maximum right degree d2max =247
Average degree d =17.870 8
Average left degree d1 =72.483 7
Average right degree d2 =10.191 8
Fill p =0.007 487 32
Average edge multiplicity m̃ =2.116 96
Size of LCC N =4,715
Diameter δ =11
50-Percentile effective diameter δ0.5 =3.398 69
90-Percentile effective diameter δ0.9 =5.191 90
Median distance δM =4
Mean distance δm =3.825 34
Gini coefficient G =0.846 088
Balanced inequality ratio P =0.146 759
Left balanced inequality ratio P1 =0.093 548 2
Right balanced inequality ratio P2 =0.191 945
Relative edge distribution entropy Her =0.784 443
Power law exponent γ =2.094 41
Tail power law exponent γt =1.731 00
Tail power law exponent with p γ3 =1.731 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.601 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =1.751 00
Right p-value p2 =0.000 00
Degree assortativity ρ =−0.308 747
Degree assortativity p-value pρ =0.000 00
Spectral norm α =335.026
Algebraic connectivity a =0.024 227 7
Spectral separation 1[A] / λ2[A]| =2.008 36
Controllability C =3,955
Relative controllability Cr =0.763 956


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.