LiveJournal
This is the social network of LiveJournal. Nodes are users of LiveJournal, and
directed edges represent friendships.
Metadata
Statistics
| Size | n = | 4,846,609
|
| Volume | m = | 68,475,391
|
| Loop count | l = | 0
|
| Wedge count | s = | 7,269,503,753
|
| Claw count | z = | 9,778,896,249,995
|
| Cross count | x = | 26,294,801,172,589,484
|
| Triangle count | t = | 285,730,264
|
| Square count | q = | 51,520,572,777
|
| Maximum degree | dmax = | 22,887
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| Maximum outdegree | d+max = | 20,292
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| Maximum indegree | d−max = | 13,905
|
| Average degree | d = | 28.257 0
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| Fill | p = | 2.915 13 × 10−6
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| Size of LCC | N = | 4,843,953
|
| Size of LSCC | Ns = | 3,828,682
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| Relative size of LSCC | Nrs = | 0.789 971
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| Diameter | δ = | 20
|
| 50-Percentile effective diameter | δ0.5 = | 4.949 60
|
| 90-Percentile effective diameter | δ0.9 = | 6.179 12
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| Median distance | δM = | 5
|
| Mean distance | δm = | 5.488 16
|
| Gini coefficient | G = | 0.715 911
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| Balanced inequality ratio | P = | 0.220 534
|
| Outdegree balanced inequality ratio | P+ = | 0.231 190
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| Indegree balanced inequality ratio | P− = | 0.226 957
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| Relative edge distribution entropy | Her = | 0.929 996
|
| Power law exponent | γ = | 1.561 69
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| Tail power law exponent | γt = | 2.651 00
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| Tail power law exponent with p | γ3 = | 2.651 00
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| p-value | p = | 0.000 00
|
| Outdegree tail power law exponent with p | γ3,o = | 2.811 00
|
| Outdegree p-value | po = | 0.000 00
|
| Indegree tail power law exponent with p | γ3,i = | 2.751 00
|
| Indegree p-value | pi = | 0.000 00
|
| Degree assortativity | ρ = | +0.021 043 4
|
| Degree assortativity p-value | pρ = | 0.000 00
|
| Clustering coefficient | c = | 0.117 916
|
| Directed clustering coefficient | c± = | 0.152 551
|
| Spectral norm | α = | 760.849
|
| Operator 2-norm | ν = | 404.861
|
| Cyclic eigenvalue | π = | 352.036
|
| Reciprocity | y = | 0.748 419
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| Non-bipartivity | bA = | 0.703 558
|
| Normalized non-bipartivity | bN = | 0.005 300 70
|
| Controllability | C = | 1,128,538
|
| Relative controllability | Cr = | 0.232 851
|
Plots
Matrix decompositions plots
Downloads
References
|
[1]
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Jérôme Kunegis.
KONECT – The Koblenz Network Collection.
In Proc. Int. Conf. on World Wide Web Companion, pages
1343–1350, 2013.
[ http ]
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[2]
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Jure Leskovec, Kevin J. Lang, Anirban Dasgupta, and Michael W. Mahoney.
Statistical properties of community structure in large social and
information networks.
In Proc. Int. World Wide Web Conf., pages 695–704, 2008.
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