Google+ (NIPS)
This directed network contains Google+ user–user links. A node represents a
user, and a directed edge denotes that one user has the other user in his
circles.
Metadata
Statistics
| Size | n = | 23,628
|
| Volume | m = | 39,242
|
| Loop count | l = | 0
|
| Wedge count | s = | 14,738,751
|
| Claw count | z = | 6,512,607,606
|
| Cross count | x = | 3,210,181,194,587
|
| Triangle count | t = | 18,221
|
| Square count | q = | 2,358,832
|
| 4-Tour count | T4 = | 77,904,048
|
| Maximum degree | dmax = | 2,771
|
| Maximum outdegree | d+max = | 2,748
|
| Maximum indegree | d−max = | 26
|
| Average degree | d = | 3.321 65
|
| Fill | p = | 7.029 36 × 10−5
|
| Size of LCC | N = | 23,613
|
| Size of LSCC | Ns = | 50
|
| Relative size of LSCC | Nrs = | 0.002 116 13
|
| Diameter | δ = | 8
|
| 50-Percentile effective diameter | δ0.5 = | 3.487 59
|
| 90-Percentile effective diameter | δ0.9 = | 4.582 91
|
| Median distance | δM = | 4
|
| Mean distance | δm = | 3.951 81
|
| Gini coefficient | G = | 0.659 896
|
| Balanced inequality ratio | P = | 0.243 374
|
| Outdegree balanced inequality ratio | P+ = | 0.284 720
|
| Indegree balanced inequality ratio | P− = | 0.372 713
|
| Relative edge distribution entropy | Her = | 0.767 492
|
| Power law exponent | γ = | 3.982 21
|
| Tail power law exponent | γt = | 2.621 00
|
| Tail power law exponent with p | γ3 = | 2.621 00
|
| p-value | p = | 0.000 00
|
| Outdegree tail power law exponent with p | γ3,o = | 1.551 00
|
| Outdegree p-value | po = | 0.000 00
|
| Indegree tail power law exponent with p | γ3,i = | 3.361 00
|
| Indegree p-value | pi = | 0.000 00
|
| Degree assortativity | ρ = | −0.388 516
|
| Degree assortativity p-value | pρ = | 0.000 00
|
| In/outdegree correlation | ρ± = | +0.056 484 8
|
| Clustering coefficient | c = | 0.003 708 79
|
| Directed clustering coefficient | c± = | 0.115 634
|
| Spectral norm | α = | 63.595 4
|
| Operator 2-norm | ν = | 59.579 0
|
| Cyclic eigenvalue | π = | 6.168 89
|
| Algebraic connectivity | a = | 0.011 436 9
|
| Spectral separation | |λ1[A] / λ2[A]| = | 1.122 67
|
| Reciprocity | y = | 0.002 446 36
|
| Non-bipartivity | bA = | 0.109 267
|
| Normalized non-bipartivity | bN = | 0.005 820 67
|
| Algebraic non-bipartivity | χ = | 0.011 413 1
|
| Spectral bipartite frustration | bK = | 0.000 859 765
|
| Controllability | C = | 23,497
|
| Relative controllability | Cr = | 0.994 456
|
Plots
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]
|
Julian McAuley and Jure Leskovec.
Learning to discover social circles in ego networks.
In Adv. in Neural Inf. Process. Syst., pages 548–556. 2012.
|
KONECT ‣ Networks ‣
Buy Me a Coffee
