Wikipedia edits (zh)

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


Internal nameedit-zhwiki
NameWikipedia edits (zh)
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 =5,339,125
Left size n1 =307,653
Right size n2 =5,031,472
Volume m =36,369,331
Unique edge count m̿ =16,545,004
Wedge count s =1,762,010,837,447
Maximum degree dmax =2,645,976
Maximum left degree d1max =2,645,976
Maximum right degree d2max =304,222
Average degree d =13.623 7
Average left degree d1 =118.215
Average right degree d2 =7.228 37
Average edge multiplicity m̃ =2.198 21
Size of LCC N =5,285,438
Diameter δ =12
50-Percentile effective diameter δ0.5 =3.469 57
90-Percentile effective diameter δ0.9 =3.978 70
Median distance δM =4
Mean distance δm =3.877 02
Gini coefficient G =0.874 229
Balanced inequality ratio P =0.124 047
Left balanced inequality ratio P1 =0.045 557 2
Right balanced inequality ratio P2 =0.187 570
Relative edge distribution entropy Her =0.729 553
Power law exponent γ =2.830 91
Tail power law exponent with p γ3 =2.031 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.681 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =2.041 00
Right p-value p2 =0.000 00
Degree assortativity ρ =−0.064 174 9
Degree assortativity p-value pρ =0.000 00
Spectral separation 1[A] / λ2[A]| =5.126 59


Degree distribution

Cumulative degree distribution

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

Hop distribution

Delaunay graph drawing

Edge weight/multiplicity distribution

Temporal distribution



[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.