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

4Tour count  T_{4} =  8,363,776

Maximum degree  d_{max} =  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  N_{s} =  3,235

Relative size of LSCC  N^{r}_{s} =  0.855 141

Diameter  δ =  10

50Percentile effective diameter  δ_{0.5} =  3.182 39

90Percentile effective diameter  δ_{0.9} =  4.424 37

Median distance  δ_{M} =  4

Mean distance  δ_{m} =  3.688 88

Gini coefficient  G =  0.703 513

Balanced inequality ratio  P =  0.221 988

Outdegree balanced inequality ratio  P_{+} =  0.225 544

Indegree balanced inequality ratio  P_{−} =  0.228 686

Relative edge distribution entropy  H_{er} =  0.861 907

Power law exponent  γ =  1.924 11

Tail power law exponent  γ_{t} =  2.091 00

Tail power law exponent with p  γ_{3} =  2.091 00

pvalue  p =  0.000 00

Outdegree tail power law exponent with p  γ_{3,o} =  2.121 00

Outdegree pvalue  p_{o} =  0.006 000 00

Indegree tail power law exponent with p  γ_{3,i} =  2.231 00

Indegree pvalue  p_{i} =  0.000 00

Degree assortativity  ρ =  −0.168 516

Degree assortativity pvalue  p_{ρ} =  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 2norm  ν =  126.098

Cyclic eigenvalue  π =  93.416 9

Algebraic connectivity  a =  0.253 239

Reciprocity  y =  0.832 052

Nonbipartivity  b_{A} =  0.516 941

Normalized nonbipartivity  b_{N} =  0.039 852 3

Spectral bipartite frustration  b_{K} =  0.002 435 24

Negativity  ζ =  0.063 507 8

Algebraic conflict  ξ =  0.140 284

Triadic conflict  τ =  0.143 562

Spectral signed frustration  φ =  0.004 771 95

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]

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.
