Wikipedia dynamic (fr)

This network shows the evolution of hyperlinks between articles of the French 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).

Metadata

CodeUf
Internal namelink-dynamic-frwiki
NameWikipedia dynamic (fr)
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Category
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

Statistics

Size n =2,212,682
Volume m =59,008,831
Unique edge count m̿ =24,440,537
Wedge count s =84,717,021,383
Claw count z =673,558,281,471,946
Cross count x =1.276 03 × 1019
Triangle count t =139,637,311
Maximum degree dmax =321,458
Maximum outdegree d+max =126,733
Maximum indegree dmax =240,733
Average degree d =53.336 9
Fill p =5.025 16 × 10−6
Average edge multiplicity m̃ =2.414 38
Size of LCC N =2,208,840
Size of LSCC Ns =1,323,072
Relative size of LSCC Nrs =0.597 949
Diameter δ =12
50-Percentile effective diameter δ0.5 =3.335 31
90-Percentile effective diameter δ0.9 =4.454 42
Mean distance δm =3.830 41
Gini coefficient G =0.774 229
Relative edge distribution entropy Her =0.883 483
Power law exponent γ =1.614 91
Tail power law exponent γt =2.391 00
Degree assortativity ρ =−0.045 824 8
Degree assortativity p-value pρ =0.000 00
Clustering coefficient c =0.004 944 84
Spectral norm α =677.907
Operator 2-norm ν =566.281
Cyclic eigenvalue π =163.465
Reciprocity y =0.155 224
Non-bipartivity bA =0.219 874
Normalized non-bipartivity bN =0.019 718 6

Plots

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

Inter-event distribution

Matrix decompositions plots

Downloads

References

[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.