Wiktionary edits (dv)

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


Internal nameedit-dvwiktionary
NameWiktionary edits (dv)
Data sourcehttp://dumps.wikimedia.org/
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 =1,361
Left size n1 =197
Right size n2 =1,164
Volume m =4,497
Unique edge count m̿ =2,131
Wedge count s =121,051
Claw count z =7,451,735
Cross count x =423,415,319
Square count q =66,886
4-Tour count T4 =1,024,014
Maximum degree dmax =1,168
Maximum left degree d1max =1,168
Maximum right degree d2max =129
Average degree d =6.608 38
Average left degree d1 =22.827 4
Average right degree d2 =3.863 40
Fill p =0.009 293 18
Average edge multiplicity m̃ =2.110 28
Size of LCC N =967
Diameter δ =12
50-Percentile effective diameter δ0.5 =3.531 95
90-Percentile effective diameter δ0.9 =5.509 69
Median distance δM =4
Mean distance δm =4.059 81
Gini coefficient G =0.763 130
Balanced inequality ratio P =0.190 794
Left balanced inequality ratio P1 =0.120 970
Right balanced inequality ratio P2 =0.247 054
Relative edge distribution entropy Her =0.819 505
Power law exponent γ =2.871 93
Tail power law exponent γt =2.041 00
Tail power law exponent with p γ3 =2.041 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.711 00
Left p-value p1 =0.149 000
Right tail power law exponent with p γ3,2 =2.151 00
Right p-value p2 =0.000 00
Degree assortativity ρ =−0.044 171 5
Degree assortativity p-value pρ =0.041 462 5
Spectral norm α =112.778
Algebraic connectivity a =0.031 638 1
Spectral separation 1[A] / λ2[A]| =1.416 47
Controllability C =826
Relative controllability Cr =0.680 395


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. http://dumps.wikimedia.org/, January 2010.