Wikipedia edits (glk)

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


Internal nameedit-glkwiki
NameWikipedia edits (glk)
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 =12,825
Left size n1 =868
Right size n2 =11,957
Volume m =36,620
Unique edge count m̿ =19,180
Wedge count s =28,118,466
Claw count z =57,506,866,552
Cross count x =96,943,064,183,460
Square count q =1,054,969
4-Tour count T4 =120,970,808
Maximum degree dmax =12,284
Maximum left degree d1max =12,284
Maximum right degree d2max =330
Average degree d =5.710 72
Average left degree d1 =42.188 9
Average right degree d2 =3.062 64
Fill p =0.001 848 02
Average edge multiplicity m̃ =1.909 28
Size of LCC N =11,885
Diameter δ =12
50-Percentile effective diameter δ0.5 =3.185 85
90-Percentile effective diameter δ0.9 =3.977 14
Median distance δM =4
Mean distance δm =3.386 20
Gini coefficient G =0.780 335
Balanced inequality ratio P =0.182 755
Left balanced inequality ratio P1 =0.083 342 4
Right balanced inequality ratio P2 =0.270 836
Relative edge distribution entropy Her =0.725 497
Power law exponent γ =4.344 42
Tail power law exponent γt =2.471 00
Tail power law exponent with p γ3 =2.471 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.711 00
Left p-value p1 =0.143 000
Right tail power law exponent with p γ3,2 =2.581 00
Right p-value p2 =0.000 00
Degree assortativity ρ =−0.396 992
Degree assortativity p-value pρ =0.000 00
Spectral norm α =298.292
Algebraic connectivity a =0.048 601 0
Spectral separation 1[A] / λ2[A]| =1.256 51
Controllability C =10,860
Relative controllability Cr =0.870 750


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.