Wikiquote edits (cs)

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


Internal nameedit-cswikiquote
NameWikiquote edits (cs)
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 =12,878
Left size n1 =1,133
Right size n2 =11,745
Volume m =64,726
Unique edge count m̿ =43,583
Wedge count s =42,940,456
Claw count z =61,966,177,113
Cross count x =87,393,929,074,201
Square count q =21,911,187
4-Tour count T4 =347,163,478
Maximum degree dmax =12,321
Maximum left degree d1max =12,321
Maximum right degree d2max =475
Average degree d =10.052 2
Average left degree d1 =57.128 0
Average right degree d2 =5.510 94
Fill p =0.003 275 17
Average edge multiplicity m̃ =1.485 12
Size of LCC N =12,552
Diameter δ =11
50-Percentile effective diameter δ0.5 =3.051 87
90-Percentile effective diameter δ0.9 =3.891 95
Median distance δM =4
Mean distance δm =3.242 10
Gini coefficient G =0.759 393
Balanced inequality ratio P =0.205 837
Left balanced inequality ratio P1 =0.071 238 8
Right balanced inequality ratio P2 =0.294 719
Relative edge distribution entropy Her =0.760 975
Power law exponent γ =2.049 38
Tail power law exponent γt =2.541 00
Tail power law exponent with p γ3 =2.541 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.701 00
Left p-value p1 =0.001 000 00
Right tail power law exponent with p γ3,2 =4.961 00
Right p-value p2 =0.105 000
Degree assortativity ρ =−0.230 983
Degree assortativity p-value pρ =0.000 00
Spectral norm α =526.620
Algebraic connectivity a =0.050 580 7
Spectral separation 1[A] / λ2[A]| =2.645 47
Controllability C =10,843
Relative controllability Cr =0.849 432


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.