Northeast USA

This is the directed road network from the 9th DIMACS Implementation Challenge, for the area "Northeast USA".

Metadata

Code9N
Internal namedimacs9-NE
NameNortheast USA
Data sourcehttp://www.diag.uniroma1.it/challenge9/download.shtml
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Category
Infrastructure network
Dataset timestamp 1991
Node meaningNode
Edge meaningRoad
Network formatUnipartite, directed
Edge typeUnweighted, no multiple edges
ReciprocalContains reciprocal edges
Directed cyclesContains directed cycles
LoopsDoes not contain loops

Statistics

Size n =1,524,453
Volume m =3,868,020
Loop count l =0
Wedge count s =3,662,100
Claw count z =26,925,368
Cross count x =25,629,408
Triangle count t =37,012
Square count q =148,092
4-Tour count T4 =19,701,156
Maximum degree dmax =18
Maximum outdegree d+max =9
Maximum indegree dmax =9
Average degree d =5.074 63
Fill p =1.664 41 × 10−6
Size of LCC N =1,524,453
Size of LSCC Ns =1,524,453
Relative size of LSCC Nrs =1.000 00
Diameter δ =2,098
50-Percentile effective diameter δ0.5 =720.652
90-Percentile effective diameter δ0.9 =1,327.23
Median distance δM =721
Mean distance δm =764.448
Gini coefficient G =0.202 056
Balanced inequality ratio P =0.432 455
Outdegree balanced inequality ratio P+ =0.432 455
Indegree balanced inequality ratio P =0.432 455
Relative edge distribution entropy Her =0.994 586
Power law exponent γ =2.189 87
Tail power law exponent γt =6.461 00
Degree assortativity ρ =+0.105 737
Degree assortativity p-value pρ =0.000 00
In/outdegree correlation ρ± =+1.000 00
Clustering coefficient c =0.030 320 3
Directed clustering coefficient c± =0.030 320 3
Spectral norm α =8.670 33
Operator 2-norm ν =4.335 17
Cyclic eigenvalue π =4.335 17
Algebraic connectivity a =5.380 07 × 10−7
Reciprocity y =1.000 00
Non-bipartivity bA =0.091 415 7
Normalized non-bipartivity bN =0.000 394 322
Algebraic non-bipartivity χ =0.000 779 372
Spectral bipartite frustration bK =7.679 10 × 10−5

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 Laplacian

Spectral graph drawing based on the normalized adjacency matrix

Hop distribution

In/outdegree scatter plot

Clustering coefficient 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 ]