Wikipedia dynamic (de)

This network shows the evolution of hyperlinks between articles of the German Wikipedia. The nodes represent articles. An edge indicates that a hyperlink was added or removed depending on the edge weight (−1 for removal or +1 for addition).


Internal namelink-dynamic-dewiki
NameWikipedia dynamic (de)
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Hyperlink network
Node meaningArticle
Edge meaningReference
Network formatUnipartite, directed
Edge typeDynamic
Temporal data Edges are annotated with timestamps
ReciprocalContains reciprocal edges
Directed cyclesContains directed cycles
LoopsContains loops


Size n =2,166,669
Volume m =86,337,879
Unique edge count m̿ =31,105,755
Loop count l =2,764
Wedge count s =69,396,476,987
Claw count z =293,022,808,383,642
Cross count x =3,823,007,956,678,213,120
Triangle count t =169,876,249
Maximum degree dmax =394,371
Maximum outdegree d+max =218,465
Maximum indegree dmax =175,906
Average degree d =79.696 4
Fill p =6.671 27 × 10−6
Average edge multiplicity m̃ =2.775 62
Size of LCC N =2,165,679
Size of LSCC Ns =1,464,096
Relative size of LSCC Nrs =0.675 736
Diameter δ =10
50-Percentile effective diameter δ0.5 =3.186 15
90-Percentile effective diameter δ0.9 =4.097 19
Median distance δM =4
Mean distance δm =3.682 59
Gini coefficient G =0.730 492
Balanced inequality ratio P =0.227 484
Outdegree balanced inequality ratio P+ =0.245 332
Indegree balanced inequality ratio P =0.197 906
Relative edge distribution entropy Her =0.903 552
Power law exponent γ =1.499 69
Degree assortativity ρ =−0.036 670 9
Degree assortativity p-value pρ =0.000 00
Clustering coefficient c =0.007 343 73
Directed clustering coefficient c± =0.023 497 1
Spectral norm α =579.773
Operator 2-norm ν =396.931
Reciprocity y =0.174 983
Non-bipartivity bA =0.386 372
Normalized non-bipartivity bN =0.022 280 9


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 normalized adjacency matrix

Hop distribution

In/outdegree scatter plot

Temporal distribution

Signed temporal distribution

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] Julia Preusse, Jérôme Kunegis, Matthias Thimm, Thomas Gottron, and Steffen Staab. Structural dynamics of knowledge networks. In Proc. Int. Conf. on Weblogs and Soc. Media, 2013.