Wikipedia edits (ace)

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


Internal nameedit-acewiki
NameWikipedia edits (ace)
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 =12,844
Left size n1 =1,321
Right size n2 =11,523
Volume m =89,021
Unique edge count m̿ =47,547
Wedge count s =30,342,600
Claw count z =29,224,816,319
Cross count x =30,512,214,738,882
Square count q =52,965,523
4-Tour count T4 =545,279,202
Maximum degree dmax =8,801
Maximum left degree d1max =8,801
Maximum right degree d2max =292
Average degree d =13.861 9
Average left degree d1 =67.389 1
Average right degree d2 =7.725 51
Fill p =0.003 123 60
Average edge multiplicity m̃ =1.872 27
Size of LCC N =11,903
Diameter δ =13
50-Percentile effective diameter δ0.5 =3.400 40
90-Percentile effective diameter δ0.9 =5.233 03
Median distance δM =4
Mean distance δm =3.835 77
Gini coefficient G =0.857 540
Balanced inequality ratio P =0.138 377
Left balanced inequality ratio P1 =0.065 883 3
Right balanced inequality ratio P2 =0.188 147
Relative edge distribution entropy Her =0.758 068
Power law exponent γ =2.452 64
Tail power law exponent γt =2.601 00
Tail power law exponent with p γ3 =2.601 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.511 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =7.651 00
Right p-value p2 =0.211 000
Degree assortativity ρ =−0.328 453
Degree assortativity p-value pρ =0.000 00
Spectral norm α =402.541
Algebraic connectivity a =0.016 597 5
Spectral separation 1[A] / λ2[A]| =2.028 99
Controllability C =10,247
Relative controllability Cr =0.818 450


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.