Digg
This is the reply network of the social news website Digg. Each node in the
network is a user of the website, and each directed edge denotes that a user
replied to another user.
Metadata
Statistics
Size  n =  30,398

Volume  m =  87,627

Unique edge count  m̿ =  86,404

Loop count  l =  1,424

Wedge count  s =  2,294,667

Claw count  z =  66,161,072

Cross count  x =  2,478,004,006

Triangle count  t =  4,282

Square count  q =  78,931

4Tour count  T_{4} =  9,980,426

Maximum degree  d_{max} =  310

Maximum outdegree  d^{+}_{max} =  259

Maximum indegree  d^{−}_{max} =  243

Average degree  d =  5.765 31

Fill  p =  9.350 69 × 10^{−5}

Average edge multiplicity  m̃ =  1.014 15

Size of LCC  N =  29,652

Size of LSCC  N_{s} =  6,746

Relative size of LSCC  N^{r}_{s} =  0.221 922

Diameter  δ =  12

50Percentile effective diameter  δ_{0.5} =  4.195 73

90Percentile effective diameter  δ_{0.9} =  5.401 91

Median distance  δ_{M} =  5

Mean distance  δ_{m} =  4.680 37

Gini coefficient  G =  0.631 648

Relative edge distribution entropy  H_{er} =  0.919 982

Power law exponent  γ =  1.987 46

Tail power law exponent  γ_{t} =  2.691 00

Degree assortativity  ρ =  +0.004 633 88

Degree assortativity pvalue  p_{ρ} =  0.055 833 5

In/outdegree correlation  ρ^{±} =  +0.157 008

Clustering coefficient  c =  0.005 598 20

Spectral norm  α =  40.400 0

Operator 2norm  ν =  26.656 7

Cyclic eigenvalue  π =  17.141 8

Algebraic connectivity  a =  0.065 238 5

Spectral separation  λ_{1}[A] / λ_{2}[A] =  1.142 43

Reciprocity  y =  0.015 520 1

Nonbipartivity  b_{A} =  0.338 291

Normalized nonbipartivity  b_{N} =  0.037 413 4

Spectral bipartite frustration  b_{K} =  0.002 814 78

Controllability  C =  16,796

Relative controllability  C_{r} =  0.552 536

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]

Munmun De Choudhury, Hari Sundaram, Ajita John, and Dorée Duncan Seligmann.
Social synchrony: Predicting mimicry of user actions in online social
media.
In Proc. Int. Conf. on Comput. Science and Engineering, pages
151–158, 2009.
