Full USA

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

Metadata

Code9U
Internal namedimacs9-USA
NameFull 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 =23,947,347
Volume m =57,708,624
Loop count l =0
Wedge count s =51,012,721
Claw count z =363,785,540
Cross count x =334,751,617
Triangle count t =438,804
Square count q =1,607,203
Maximum degree dmax =18
Maximum outdegree d+max =9
Maximum indegree dmax =9
Average degree d =4.819 63
Fill p =1.006 30 × 10−7
Size of LCC N =23,947,347
Size of LSCC Ns =23,947,347
Relative size of LSCC Nrs =1.000 00
Diameter δ =8,440
50-Percentile effective diameter δ0.5 =2,722.35
90-Percentile effective diameter δ0.9 =5,034.32
Median distance δM =2,723
Mean distance δm =2,893.58
Balanced inequality ratio P =0.418 964
Outdegree balanced inequality ratio P+ =0.418 964
Indegree balanced inequality ratio P =0.418 964
Tail power law exponent with p γ3 =6.541 00
p-value p =0.000 00
Outdegree tail power law exponent with p γ3,o =6.541 00
Outdegree p-value po =0.000 00
Indegree tail power law exponent with p γ3,i =6.541 00
Indegree p-value pi =0.000 00
Degree assortativity ρ =+0.067 358 4
Degree assortativity p-value pρ =0.000 00
Clustering coefficient c =0.025 805 6
Operator 2-norm ν =4.519 83
Algebraic connectivity a =3.028 22 × 10−8
Reciprocity y =1.000 00
Non-bipartivity bA =0.125 732
Normalized non-bipartivity bN =6.231 10 × 10−5

Plots

Degree distribution

Cumulative degree distribution

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

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 ]