Similarities (DBpedia)

This is the similarity graph from DBpedia. It contains the "similar to" links between pages of Wikipedia. The network is undirected and does not contain multiple edges. The "similar to" relationship was removed from DBpedia at a specific version. Thus, this dataset will not be updated with new versions of DBpedia. The edges correspond to the <> relationship type in DBpedia.


Internal namedbpedia-similar
NameSimilarities (DBpedia)
Data source
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Miscellaneous network
Dataset timestamp 2001 ⋯ 2017
Node meaningConcept
Edge meaningSimilarity
Network formatUnipartite, undirected
Edge typeUnweighted, no multiple edges
LoopsContains loops


Size n =430
Volume m =565
Loop count l =1
Wedge count s =2,993
Claw count z =9,966
Cross count x =27,882
Triangle count t =708
Square count q =5,819
4-Tour count T4 =59,652
Maximum degree dmax =16
Average degree d =2.627 91
Fill p =0.006 097 23
Size of LCC N =107
Diameter δ =14
50-Percentile effective diameter δ0.5 =3.752 62
90-Percentile effective diameter δ0.9 =6.874 16
Median distance δM =4
Mean distance δm =4.501 76
Gini coefficient G =0.467 541
Balanced inequality ratio P =0.318 584
Relative edge distribution entropy Her =0.927 887
Power law exponent γ =2.674 66
Tail power law exponent γt =2.301 00
Tail power law exponent with p γ3 =2.301 00
p-value p =0.037 000 0
Degree assortativity ρ =+0.733 007
Degree assortativity p-value pρ =1.187 60 × 10−190
Clustering coefficient c =0.709 656
Spectral norm α =15.000 0
Algebraic connectivity a =0.021 683 8
Spectral separation 1[A] / λ2[A]| =2.244 37
Non-bipartivity bA =0.676 315
Normalized non-bipartivity bN =0.067 790 0
Algebraic non-bipartivity χ =0.130 995
Spectral bipartite frustration bK =0.010 491 4
Controllability C =80
Relative controllability Cr =0.186 047


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

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 ]
[2] Sören Auer, Christian Bizer, Georgi Kobilarov, Jens Lehmann, Richard Cyganiak, and Zachary Ives. DBpedia: A nucleus for a web of open data. In Proc. Int. Semant. Web Conf., pages 722–735, 2008.