Wikipedia edits (ug)

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


Internal nameedit-ugwiki
NameWikipedia edits (ug)
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 =12,183
Left size n1 =1,102
Right size n2 =11,081
Volume m =116,274
Unique edge count m̿ =55,347
Wedge count s =33,902,617
Claw count z =20,514,180,121
Cross count x =10,950,231,379,116
Square count q =114,015,894
4-Tour count T4 =1,047,862,790
Maximum degree dmax =12,168
Maximum left degree d1max =12,168
Maximum right degree d2max =406
Average degree d =19.087 9
Average left degree d1 =105.512
Average right degree d2 =10.493 1
Fill p =0.004 532 46
Average edge multiplicity m̃ =2.100 82
Size of LCC N =11,137
Diameter δ =14
50-Percentile effective diameter δ0.5 =3.465 55
90-Percentile effective diameter δ0.9 =5.430 73
Median distance δM =4
Mean distance δm =4.000 69
Gini coefficient G =0.863 823
Balanced inequality ratio P =0.141 364
Left balanced inequality ratio P1 =0.057 433 3
Right balanced inequality ratio P2 =0.175 585
Relative edge distribution entropy Her =0.754 649
Power law exponent γ =2.309 95
Tail power law exponent γt =1.821 00
Tail power law exponent with p γ3 =1.821 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.661 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =8.911 00
Right p-value p2 =0.124 000
Degree assortativity ρ =−0.212 250
Degree assortativity p-value pρ =0.000 00
Spectral norm α =557.331
Algebraic connectivity a =0.005 644 07
Spectral separation 1[A] / λ2[A]| =2.017 54
Controllability C =9,755
Relative controllability Cr =0.824 668


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.