Bitcoin Alpha
This is a user–user trust/distrust network, from the Bitcoin Alpha platform,
on which Bitcoins are traded. Each directed edge represents trust or distrust
on a scale from −10 to +10. Positive edge weights denote trust, and negative
edge weights denote distrust. An edge weight of zero does not appear.
Metadata
Statistics
Size | n = | 3,783
|
Volume | m = | 24,186
|
Loop count | l = | 0
|
Wedge count | s = | 851,958
|
Claw count | z = | 282,238,264
|
Cross count | x = | 39,076,718,662
|
Triangle count | t = | 22,153
|
Square count | q = | 615,962
|
4-Tour count | T4 = | 8,363,776
|
Maximum degree | dmax = | 888
|
Maximum outdegree | d+max = | 490
|
Maximum indegree | d−max = | 398
|
Average degree | d = | 12.786 7
|
Fill | p = | 0.001 690 46
|
Size of LCC | N = | 3,775
|
Size of LSCC | Ns = | 3,235
|
Relative size of LSCC | Nrs = | 0.855 141
|
Diameter | δ = | 10
|
50-Percentile effective diameter | δ0.5 = | 3.182 39
|
90-Percentile effective diameter | δ0.9 = | 4.424 37
|
Median distance | δM = | 4
|
Mean distance | δm = | 3.688 88
|
Gini coefficient | G = | 0.703 513
|
Balanced inequality ratio | P = | 0.221 988
|
Outdegree balanced inequality ratio | P+ = | 0.225 544
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Indegree balanced inequality ratio | P− = | 0.228 686
|
Relative edge distribution entropy | Her = | 0.861 907
|
Power law exponent | γ = | 1.924 11
|
Tail power law exponent | γt = | 2.091 00
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Tail power law exponent with p | γ3 = | 2.091 00
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p-value | p = | 0.000 00
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Outdegree tail power law exponent with p | γ3,o = | 2.121 00
|
Outdegree p-value | po = | 0.006 000 00
|
Indegree tail power law exponent with p | γ3,i = | 2.231 00
|
Indegree p-value | pi = | 0.000 00
|
Degree assortativity | ρ = | −0.168 516
|
Degree assortativity p-value | pρ = | 5.632 93 × 10−179
|
In/outdegree correlation | ρ± = | +0.917 288
|
Clustering coefficient | c = | 0.078 007 4
|
Directed clustering coefficient | c± = | 0.071 794 6
|
Spectral norm | α = | 215.586
|
Operator 2-norm | ν = | 126.098
|
Cyclic eigenvalue | π = | 93.416 9
|
Algebraic connectivity | a = | 0.253 239
|
Spectral separation | |λ1[A] / λ2[A]| = | 1.373 80
|
Reciprocity | y = | 0.832 052
|
Non-bipartivity | bA = | 0.516 941
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Normalized non-bipartivity | bN = | 0.039 852 3
|
Algebraic non-bipartivity | χ = | 0.072 870 2
|
Spectral bipartite frustration | bK = | 0.002 435 24
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Negativity | ζ = | 0.063 507 8
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Algebraic conflict | ξ = | 0.140 284
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Triadic conflict | τ = | 0.143 562
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Spectral signed frustration | φ = | 0.004 771 95
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Controllability | C = | 1,817
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Relative controllability | Cr = | 0.480 307
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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 ]
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[2]
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Srijan Kumar, Francesca Spezzano, V. S. Subrahmanian, and Christos Faloutsos.
Edge weight prediction in weighted signed networks.
In Proc. Int. Conf. Data Min., pages 221–230, 2016.
|