Wikipedia edits (gan)

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


Internal nameedit-ganwiki
NameWikipedia edits (gan)
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 =34,354
Left size n1 =1,186
Right size n2 =33,168
Volume m =382,174
Unique edge count m̿ =202,398
Wedge count s =746,639,483
Claw count z =3,093,315,623,066
Cross count x =12,553,852,725,862,754
Square count q =1,788,857,578
4-Tour count T4 =17,298,091,972
Maximum degree dmax =51,478
Maximum left degree d1max =51,478
Maximum right degree d2max =266
Average degree d =22.249 2
Average left degree d1 =322.238
Average right degree d2 =11.522 4
Fill p =0.005 145 20
Average edge multiplicity m̃ =1.888 23
Size of LCC N =33,650
Diameter δ =12
50-Percentile effective diameter δ0.5 =1.906 70
90-Percentile effective diameter δ0.9 =3.810 59
Median distance δM =2
Mean distance δm =2.905 18
Gini coefficient G =0.816 801
Balanced inequality ratio P =0.191 889
Left balanced inequality ratio P1 =0.037 247 4
Right balanced inequality ratio P2 =0.251 378
Relative edge distribution entropy Her =0.717 731
Power law exponent γ =2.001 79
Tail power law exponent γt =4.071 00
Tail power law exponent with p γ3 =4.071 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.371 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =7.861 00
Right p-value p2 =0.533 000
Degree assortativity ρ =−0.491 832
Degree assortativity p-value pρ =0.000 00
Spectral norm α =844.454
Algebraic connectivity a =0.050 884 5
Spectral separation 1[A] / λ2[A]| =1.846 86
Controllability C =32,118
Relative controllability Cr =0.937 259


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.