Twitter (ICWSM)
This is the directed network containing information about who follows whom on
Twitter. Nodes represent users and an edge shows that the left user follows the
right one.
Metadata
Statistics
Size  n =  465,017

Volume  m =  834,797

Loop count  l =  0

Wedge count  s =  187,988,707

Claw count  z =  28,887,087,190

Cross count  x =  3,417,980,886,457

Triangle count  t =  38,389

Square count  q =  21,828,900

4Tour count  T_{4} =  928,253,108

Maximum degree  d_{max} =  678

Maximum outdegree  d^{+}_{max} =  500

Maximum indegree  d^{−}_{max} =  199

Average degree  d =  3.590 39

Fill  p =  3.860 51 × 10^{−6}

Size of LCC  N =  465,017

Size of LSCC  N_{s} =  1,726

Relative size of LSCC  N^{r}_{s} =  0.003 711 69

Diameter  δ =  8

50Percentile effective diameter  δ_{0.5} =  4.065 65

90Percentile effective diameter  δ_{0.9} =  4.962 07

Mean distance  δ_{m} =  4.594 85

Gini coefficient  G =  0.694 849

Balanced inequality ratio  P =  0.220 847

Outdegree balanced inequality ratio  P_{+} =  0.404 595

Indegree balanced inequality ratio  P_{−} =  0.356 506

Relative edge distribution entropy  H_{er} =  0.822 520

Power law exponent  γ =  4.358 34

Tail power law exponent  γ_{t} =  2.471 00

Tail power law exponent with p  γ_{3} =  2.471 00

pvalue  p =  0.000 00

Outdegree tail power law exponent with p  γ_{3,o} =  1.361 00

Outdegree pvalue  p_{o} =  0.000 00

Indegree tail power law exponent with p  γ_{3,i} =  2.551 00

Indegree pvalue  p_{i} =  0.000 00

Degree assortativity  ρ =  −0.877 715

Degree assortativity pvalue  p_{ρ} =  0.000 00

In/outdegree correlation  ρ^{±} =  +0.059 352 6

Clustering coefficient  c =  0.000 612 627

Spectral norm  α =  81.599 7

Operator 2norm  ν =  79.115 0

Cyclic eigenvalue  π =  6.178 14

Algebraic connectivity  a =  0.007 317 00

Spectral separation  λ_{1}[A] / λ_{2}[A] =  1.050 05

Reciprocity  y =  0.003 011 51

Nonbipartivity  b_{A} =  0.046 055 0

Normalized nonbipartivity  b_{N} =  0.003 658 47

Spectral bipartite frustration  b_{K} =  0.000 509 603

Controllability  C =  462,515

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, YuRu Lin, Hari Sundaram, K. Selçuk Candan, Lexing Xie,
and Aisling Kelliher.
How does the data sampling strategy impact the discovery of
information diffusion in social media?
In ICWSM, pages 34–41, 2010.
