Wikinews edits (cs)

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


Internal nameedit-cswikinews
NameWikinews 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 =10,943
Left size n1 =539
Right size n2 =10,404
Volume m =47,698
Unique edge count m̿ =27,691
Wedge count s =43,130,853
Claw count z =77,736,340,986
Cross count x =116,993,431,332,978
Square count q =14,449,235
4-Tour count T4 =288,203,322
Maximum degree dmax =11,723
Maximum left degree d1max =11,723
Maximum right degree d2max =1,236
Average degree d =8.717 54
Average left degree d1 =88.493 5
Average right degree d2 =4.584 58
Fill p =0.004 937 98
Average edge multiplicity m̃ =1.722 51
Size of LCC N =10,740
Diameter δ =10
50-Percentile effective diameter δ0.5 =1.999 63
90-Percentile effective diameter δ0.9 =3.831 80
Median distance δM =2
Mean distance δm =2.978 29
Gini coefficient G =0.744 755
Balanced inequality ratio P =0.214 087
Left balanced inequality ratio P1 =0.064 111 7
Right balanced inequality ratio P2 =0.311 250
Relative edge distribution entropy Her =0.722 515
Power law exponent γ =2.382 83
Tail power law exponent γt =2.321 00
Tail power law exponent with p γ3 =2.321 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.651 00
Left p-value p1 =0.003 000 00
Right tail power law exponent with p γ3,2 =5.901 00
Right p-value p2 =0.111 000
Degree assortativity ρ =−0.281 242
Degree assortativity p-value pρ =0.000 00
Spectral norm α =505.724
Algebraic connectivity a =0.041 027 0
Spectral separation 1[A] / λ2[A]| =2.686 92
Controllability C =9,959
Relative controllability Cr =0.910 412


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.