Wikipedia edits (wuu)

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


Internal nameedit-wuuwiki
NameWikipedia edits (wuu)
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 =18,033
Left size n1 =2,447
Right size n2 =15,586
Volume m =145,064
Unique edge count m̿ =64,413
Wedge count s =32,582,768
Claw count z =18,027,800,202
Cross count x =9,078,232,761,116
Square count q =76,799,207
4-Tour count T4 =744,887,090
Maximum degree dmax =9,290
Maximum left degree d1max =9,290
Maximum right degree d2max =869
Average degree d =16.088 7
Average left degree d1 =59.282 4
Average right degree d2 =9.307 33
Fill p =0.001 688 90
Average edge multiplicity m̃ =2.252 09
Size of LCC N =16,953
Diameter δ =11
50-Percentile effective diameter δ0.5 =3.523 17
90-Percentile effective diameter δ0.9 =4.663 35
Median distance δM =4
Mean distance δm =3.981 37
Gini coefficient G =0.859 326
Balanced inequality ratio P =0.138 015
Left balanced inequality ratio P1 =0.057 857 2
Right balanced inequality ratio P2 =0.183 953
Relative edge distribution entropy Her =0.770 057
Power law exponent γ =2.436 61
Tail power law exponent γt =1.881 00
Tail power law exponent with p γ3 =1.881 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.481 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =6.381 00
Right p-value p2 =0.364 000
Degree assortativity ρ =−0.161 182
Degree assortativity p-value pρ =0.000 00
Spectral norm α =536.947
Algebraic connectivity a =0.059 973 0
Spectral separation 1[A] / λ2[A]| =1.418 56
Controllability C =14,401
Relative controllability Cr =0.813 340


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

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.