Wikipedia edits (haw)

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


Internal nameedit-hawwiki
NameWikipedia edits (haw)
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 =4,784
Left size n1 =844
Right size n2 =3,940
Volume m =65,031
Unique edge count m̿ =32,164
Wedge count s =13,325,652
Claw count z =5,656,146,038
Cross count x =2,082,466,998,729
Square count q =49,603,367
4-Tour count T4 =450,200,324
Maximum degree dmax =7,028
Maximum left degree d1max =7,028
Maximum right degree d2max =311
Average degree d =27.186 9
Average left degree d1 =77.050 9
Average right degree d2 =16.505 3
Fill p =0.009 672 34
Average edge multiplicity m̃ =2.021 86
Size of LCC N =4,117
Diameter δ =13
50-Percentile effective diameter δ0.5 =3.378 97
90-Percentile effective diameter δ0.9 =5.480 77
Median distance δM =4
Mean distance δm =3.883 33
Gini coefficient G =0.791 394
Balanced inequality ratio P =0.198 367
Left balanced inequality ratio P1 =0.075 379 4
Right balanced inequality ratio P2 =0.262 552
Relative edge distribution entropy Her =0.792 599
Power law exponent γ =1.754 15
Tail power law exponent γt =1.871 00
Tail power law exponent with p γ3 =1.871 00
p-value p =0.034 000 0
Left tail power law exponent with p γ3,1 =1.631 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =3.261 00
Right p-value p2 =0.000 00
Degree assortativity ρ =−0.232 760
Degree assortativity p-value pρ =0.000 00
Spectral norm α =419.288
Algebraic connectivity a =0.029 770 0
Spectral separation 1[A] / λ2[A]| =2.748 11
Controllability C =3,150
Relative controllability Cr =0.669 643


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.