Wikipedia edits (ay)

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


Internal nameedit-aywiki
NameWikipedia edits (ay)
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 =8,649
Left size n1 =1,231
Right size n2 =7,418
Volume m =74,029
Unique edge count m̿ =37,546
Wedge count s =18,243,853
Claw count z =12,415,042,713
Cross count x =8,979,327,668,200
Square count q =35,683,887
4-Tour count T4 =358,532,868
Maximum degree dmax =5,036
Maximum left degree d1max =5,036
Maximum right degree d2max =258
Average degree d =17.118 5
Average left degree d1 =60.137 3
Average right degree d2 =9.979 64
Fill p =0.004 111 68
Average edge multiplicity m̃ =1.971 69
Size of LCC N =7,757
Diameter δ =13
50-Percentile effective diameter δ0.5 =3.189 15
90-Percentile effective diameter δ0.9 =5.002 18
Median distance δM =4
Mean distance δm =3.558 69
Gini coefficient G =0.848 837
Balanced inequality ratio P =0.143 140
Left balanced inequality ratio P1 =0.066 690 1
Right balanced inequality ratio P2 =0.186 913
Relative edge distribution entropy Her =0.771 832
Power law exponent γ =2.136 83
Tail power law exponent γt =1.741 00
Tail power law exponent with p γ3 =1.741 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.731 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =1.751 00
Right p-value p2 =0.000 00
Degree assortativity ρ =−0.387 683
Degree assortativity p-value pρ =0.000 00
Spectral norm α =381.546
Algebraic connectivity a =0.024 150 9
Spectral separation 1[A] / λ2[A]| =2.237 79
Controllability C =6,299
Relative controllability Cr =0.735 607


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.