Facebook (WOSN)
This undirected network contains friendship data of Facebook users. A node
represents a user and an edge represents a friendship between two users. The
dataset is obviously not complete and contains a very small subset of the total
Facebook friendship graph.
Metadata
Statistics
Size  n =  63,731

Volume  m =  817,035

Wedge count  s =  71,097,140

Claw count  z =  4,499,481,578

Cross count  x =  422,832,581,040

Triangle count  t =  3,500,542

Square count  q =  151,719,237

4Tour count  T_{4} =  1,499,776,526

Maximum degree  d_{max} =  1,098

Average degree  d =  25.640 1

Fill  p =  0.000 402 324

Size of LCC  N =  63,392

Diameter  δ =  15

50Percentile effective diameter  δ_{0.5} =  3.748 16

90Percentile effective diameter  δ_{0.9} =  4.968 12

Mean distance  δ_{m} =  4.309 73

Gini coefficient  G =  0.642 926

Relative edge distribution entropy  H_{er} =  0.931 429

Power law exponent  γ =  1.432 97

Tail power law exponent  γ_{t} =  2.941 00

Degree assortativity  ρ =  +0.177 015

Degree assortativity pvalue  p_{ρ} =  0.000 00

Clustering coefficient  c =  0.147 708

Spectral norm  α =  132.568

Algebraic connectivity  a =  0.046 404 4

Spectral separation  λ_{1}[A] / λ_{2}[A] =  1.243 97

Nonbipartivity  b_{A} =  0.629 659

Normalized nonbipartivity  b_{N} =  0.031 728 7

Spectral bipartite frustration  b_{K} =  0.000 572 101

Controllability  C =  1,821

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]

Bimal Viswanath, Alan Mislove, Meeyoung Cha, and Krishna P. Gummadi.
On the evolution of user interaction in Facebook.
In Proc. Workshop on Online Soc. Netw., pages 37–42, 2009.
