Italian CNR

This is a small version of the hyperlink network of the Italian CNR domain, i.e., the website of the Italian National Research Council (Consiglio Nazionale delle Ricerche).

Metadata

CodeIC
Internal namedimacs10-cnr-2000
NameItalian CNR
Data sourcehttps://www.cc.gatech.edu/dimacs10/archive/clustering.shtml
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Category
Hyperlink network
Dataset timestamp 2000
Node meaningPage
Edge meaningHyperlink
Network formatUnipartite, undirected
Edge typeUnweighted, no multiple edges
LoopsDoes not contain loops
Snapshot Is a snapshot and likely to not contain all data
Orientation Is not directed, but the underlying data is
Multiplicity Does not have multiple edges, but the underlying data has

Statistics

Size n =325,557
Volume m =2,738,969
Loop count l =0
Wedge count s =7,861,227,192
Claw count z =41,558,033,579,633
Cross count x =177,289,946,906,573,600
Triangle count t =20,977,629
Square count q =81,330,781,033
4-Tour count T4 =682,096,634,970
Maximum degree dmax =18,236
Average degree d =16.826 4
Fill p =5.168 50 × 10−5
Size of LCC N =325,557
Diameter δ =34
50-Percentile effective diameter δ0.5 =8.594 52
90-Percentile effective diameter δ0.9 =14.406 9
Median distance δM =9
Mean distance δm =9.596 26
Gini coefficient G =0.734 246
Balanced inequality ratio P =0.214 987
Relative edge distribution entropy Her =0.849 624
Power law exponent γ =1.608 09
Tail power law exponent γt =2.861 00
Tail power law exponent with p γ3 =2.861 00
p-value p =0.000 00
Degree assortativity ρ =−0.215 303
Degree assortativity p-value pρ =0.000 00
Clustering coefficient c =0.008 005 48
Spectral norm α =726.039
Algebraic connectivity a =8.710 70 × 10−6
Spectral separation |λ1[A] / λ2[A]| =1.027 46
Non-bipartivity bA =0.026 725 7
Normalized non-bipartivity bN =0.000 102 737
Algebraic non-bipartivity χ =0.000 209 185
Spectral bipartite frustration bK =3.108 00 × 10−6
Controllability C =156,427
Relative controllability Cr =0.480 490

Plots

Fruchterman–Reingold graph drawing

Degree distribution

Cumulative degree distribution

Spectral distribution of the 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

Delaunay graph drawing

Clustering coefficient distribution

Average neighbor degree distribution

SynGraphy

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] Paolo Boldi, Bruno Codenotti, Massimo Santini, and Sebastiano Vigna. UbiCrawler: A scalable fully distributed web crawler. Softw.: Pract. and Exp., 34(8):711–726, 2004.