Wikipedia edits (pap)

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


Internal nameedit-papwiki
NameWikipedia edits (pap)
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 =5,341
Left size n1 =914
Right size n2 =4,427
Volume m =61,014
Unique edge count m̿ =27,033
Wedge count s =6,358,812
Claw count z =1,536,828,934
Cross count x =358,953,428,781
Square count q =21,235,118
4-Tour count T4 =195,370,514
Maximum degree dmax =4,841
Maximum left degree d1max =4,841
Maximum right degree d2max =256
Average degree d =22.847 4
Average left degree d1 =66.754 9
Average right degree d2 =13.782 2
Fill p =0.006 680 95
Average edge multiplicity m̃ =2.257 02
Size of LCC N =4,629
Diameter δ =14
50-Percentile effective diameter δ0.5 =3.594 95
90-Percentile effective diameter δ0.9 =5.560 48
Median distance δM =4
Mean distance δm =4.204 64
Gini coefficient G =0.824 473
Balanced inequality ratio P =0.173 165
Left balanced inequality ratio P1 =0.079 735 8
Right balanced inequality ratio P2 =0.205 789
Relative edge distribution entropy Her =0.798 591
Power law exponent γ =1.984 77
Tail power law exponent γt =2.391 00
Tail power law exponent with p γ3 =2.391 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.651 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =5.441 00
Right p-value p2 =0.007 000 00
Degree assortativity ρ =−0.009 473 55
Degree assortativity p-value pρ =0.119 333
Spectral norm α =381.362
Algebraic connectivity a =0.026 554 3
Spectral separation 1[A] / λ2[A]| =1.935 52
Controllability C =3,457
Relative controllability Cr =0.672 437


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.