Wikipedia edits (zh-yue)

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


Internal nameedit-zh_yuewiki
NameWikipedia edits (zh-yue)
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 =160,909
Left size n1 =10,433
Right size n2 =150,476
Volume m =947,552
Unique edge count m̿ =473,904
Wedge count s =2,105,881,124
Claw count z =13,892,847,708,665
Cross count x =91,067,965,048,299,552
Square count q =3,041,045,418
4-Tour count T4 =32,752,994,956
Maximum degree dmax =58,016
Maximum left degree d1max =58,016
Maximum right degree d2max =1,581
Average degree d =11.777 5
Average left degree d1 =90.822 6
Average right degree d2 =6.297 03
Fill p =0.000 301 866
Average edge multiplicity m̃ =1.999 46
Size of LCC N =153,487
Diameter δ =13
50-Percentile effective diameter δ0.5 =3.505 37
90-Percentile effective diameter δ0.9 =5.207 56
Median distance δM =4
Mean distance δm =4.040 10
Gini coefficient G =0.855 344
Balanced inequality ratio P =0.138 977
Left balanced inequality ratio P1 =0.052 339 1
Right balanced inequality ratio P2 =0.193 332
Power law exponent γ =2.698 48
Tail power law exponent γt =1.981 00
Tail power law exponent with p γ3 =1.981 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.691 00
Left p-value p1 =0.077 000 0
Right tail power law exponent with p γ3,2 =2.001 00
Right p-value p2 =0.000 00
Degree assortativity ρ =−0.139 840
Degree assortativity p-value pρ =0.000 00
Spectral norm α =1,296.30
Algebraic connectivity a =0.006 260 89
Spectral separation 1[A] / λ2[A]| =1.006 82
Controllability C =139,814
Relative controllability Cr =0.887 049


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

Edge weight/multiplicity distribution

Temporal 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.