Wikipedia edits (nds)

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


Internal nameedit-ndswiki
NameWikipedia edits (nds)
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 =75,201
Left size n1 =3,689
Right size n2 =71,512
Volume m =736,112
Unique edge count m̿ =328,815
Wedge count s =1,751,590,745
Claw count z =9,728,930,640,509
Cross count x =48,651,470,287,529,624
Square count q =3,738,665,595
4-Tour count T4 =36,917,094,194
Maximum degree dmax =55,001
Maximum left degree d1max =55,001
Maximum right degree d2max =2,835
Average degree d =19.577 2
Average left degree d1 =199.542
Average right degree d2 =10.293 5
Fill p =0.001 246 42
Average edge multiplicity m̃ =2.238 68
Size of LCC N =74,059
Diameter δ =11
50-Percentile effective diameter δ0.5 =3.274 72
90-Percentile effective diameter δ0.9 =3.926 06
Median distance δM =4
Mean distance δm =3.442 37
Gini coefficient G =0.873 106
Balanced inequality ratio P =0.141 832
Left balanced inequality ratio P1 =0.028 794 5
Right balanced inequality ratio P2 =0.187 041
Relative edge distribution entropy Her =0.705 872
Power law exponent γ =2.326 21
Tail power law exponent γt =3.251 00
Tail power law exponent with p γ3 =3.251 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =1.791 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =5.421 00
Right p-value p2 =0.000 00
Degree assortativity ρ =−0.453 461
Degree assortativity p-value pρ =0.000 00
Spectral norm α =2,117.05
Algebraic connectivity a =0.012 878 1


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

Edge weight/multiplicity distribution

Temporal 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.