Wikipedia links (gan)

This network consists of the wikilinks of the Wikipedia in the Gan Chinese language (gan). Nodes are Wikipedia articles, and directed edges are wikilinks, i.e., hyperlinks within one wiki. In the wiki source, these are indicated with [[double brackets]]. Only pages in the article namespace are included.


Internal namewikipedia_link_gan
NameWikipedia links (gan)
Data source
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Hyperlink network
Node meaningArticle
Edge meaningWikilink
Network formatUnipartite, directed
Edge typeUnweighted, no multiple edges
ReciprocalContains reciprocal edges
Directed cyclesContains directed cycles
LoopsContains loops


Size n =9,179
Volume m =176,126
Loop count l =5
Wedge count s =13,304,853
Claw count z =4,227,306,917
Cross count x =1,225,630,492,890
Triangle count t =1,694,571
Square count q =123,836,297
4-Tour count T4 =1,044,138,120
Maximum degree dmax =2,086
Maximum outdegree d+max =360
Maximum indegree dmax =2,081
Average degree d =38.375 9
Fill p =0.002 090 42
Size of LCC N =9,082
Size of LSCC Ns =5,202
Relative size of LSCC Nrs =0.566 728
Diameter δ =12
50-Percentile effective diameter δ0.5 =3.526 43
90-Percentile effective diameter δ0.9 =4.969 37
Median distance δM =4
Mean distance δm =4.040 67
Gini coefficient G =0.683 585
Relative edge distribution entropy Her =0.901 168
Power law exponent γ =1.465 63
Tail power law exponent γt =2.341 00
Degree assortativity ρ =−0.073 260 2
Degree assortativity p-value pρ =3.434 22 × 10−269
In/outdegree correlation ρ± =+0.844 504
Clustering coefficient c =0.382 095
Directed clustering coefficient c± =0.709 646
Spectral norm α =258.010
Operator 2-norm ν =133.136
Cyclic eigenvalue π =124.678
Algebraic connectivity a =0.021 616 8
Reciprocity y =0.703 559
Non-bipartivity bA =0.757 868
Normalized non-bipartivity bN =0.024 953 0
Spectral bipartite frustration bK =0.000 451 332


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

In/outdegree scatter plot

Clustering coefficient distribution

Average neighbor degree 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 ]