Wikipedia edits (pdc)

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


Internal nameedit-pdcwiki
NameWikipedia edits (pdc)
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 =6,592
Left size n1 =1,138
Right size n2 =5,454
Volume m =87,558
Unique edge count m̿ =36,764
Wedge count s =14,543,621
Claw count z =6,633,200,539
Cross count x =2,947,929,237,594
Square count q =35,970,586
4-Tour count T4 =346,056,296
Maximum degree dmax =12,096
Maximum left degree d1max =12,096
Maximum right degree d2max =354
Average degree d =26.564 9
Average left degree d1 =76.940 2
Average right degree d2 =16.053 9
Fill p =0.005 923 32
Average edge multiplicity m̃ =2.381 62
Size of LCC N =6,018
Diameter δ =13
50-Percentile effective diameter δ0.5 =3.112 16
90-Percentile effective diameter δ0.9 =4.458 16
Median distance δM =4
Mean distance δm =3.467 47
Gini coefficient G =0.826 697
Balanced inequality ratio P =0.170 344
Left balanced inequality ratio P1 =0.071 781 0
Right balanced inequality ratio P2 =0.222 515
Relative edge distribution entropy Her =0.790 216
Power law exponent γ =1.864 81
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 =1.671 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =4.651 00
Right p-value p2 =0.013 000 0
Degree assortativity ρ =−0.251 276
Degree assortativity p-value pρ =0.000 00
Spectral norm α =526.348
Algebraic connectivity a =0.051 608 7
Spectral separation 1[A] / λ2[A]| =2.074 77
Controllability C =4,430
Relative controllability Cr =0.678 200


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.