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.


Internal namefacebook-wosn-links
NameFacebook (WOSN)
Data sourcehttp://socialnetworks.mpi-sws.org/data-wosn2009.html
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Online social network
Dataset timestamp 2009
Node meaningUser
Edge meaningFriendship
Network formatUnipartite, undirected
Edge typeUnweighted, no multiple edges
Temporal data Edges are annotated with timestamps
LoopsDoes not contain loops
Snapshot Is a snapshot and likely to not contain all data


Size n =63,731
Volume m =817,035
Loop count l =0
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
4-Tour count T4 =1,499,776,526
Maximum degree dmax =1,098
Average degree d =25.640 1
Fill p =0.000 402 324
Size of LCC N =63,392
Diameter δ =15
50-Percentile effective diameter δ0.5 =3.748 16
90-Percentile effective diameter δ0.9 =4.968 12
Median distance δM =4
Mean distance δm =4.309 73
Gini coefficient G =0.642 926
Balanced inequality ratio P =0.249 527
Relative edge distribution entropy Her =0.931 429
Power law exponent γ =1.432 97
Tail power law exponent γt =2.941 00
Degree assortativity ρ =+0.177 015
Degree assortativity p-value pρ =0.000 00
Clustering coefficient c =0.147 708
Spectral norm α =132.568
Algebraic connectivity a =0.046 404 4
Spectral separation 1[A] / λ2[A]| =1.243 97
Non-bipartivity bA =0.629 659
Normalized non-bipartivity bN =0.031 728 7
Spectral bipartite frustration bK =0.000 572 139
Controllability C =1,821


Degree distribution

Cumulative degree distribution

Lorenz curve

Spectral distribution of the adjacency matrix

Spectral distribution of the normalized adjacency matrix

Spectral distribution of the Laplacian

Spectral graph drawing based on the adjacency matrix

Spectral graph drawing based on the Laplacian

Spectral graph drawing based on the normalized adjacency matrix

Degree assortativity

Zipf plot

Hop distribution

Clustering coefficient distribution

Average neighbor degree distribution

Temporal distribution

Temporal hop distribution

Diameter/density evolution


Inter-event distribution

Node-level inter-event distribution

Matrix decompositions plots



[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.