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

Code		`Ol`
Internal name		`facebook-wosn-links`
Name		Facebook (WOSN)
Data source		http://socialnetworks.mpi-sws.org/data-wosn2009.html
Availability		Dataset is available for download
Consistency check		Dataset passed all tests
Category		Online social network
Dataset timestamp		2009
Node meaning		User
Edge meaning		Friendship
Network format		Unipartite, undirected
Edge type		Unweighted, no multiple edges
Temporal data		Edges are annotated with timestamps
Loops		Does not contain loops
Snapshot		Is a snapshot and likely to not contain all data

Statistics

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	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
50-Percentile effective diameter	δ_0.5 =	3.748 16
90-Percentile effective diameter	δ_0.9 =	4.968 12
Median distance	δ_M =	4
Mean distance	δ_m =	4.309 73
Gini coefficient	G =	0.642 926
Balanced inequality ratio	P =	0.249 527
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
Tail power law exponent with p	γ₃ =	2.941 00
p-value	p =	0.000 00
Degree assortativity	ρ =	+0.177 015
Degree assortativity p-value	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	\|λ₁[A] / λ₂[A]\| =	1.241 96
Normalized non-bipartivity	b_N =	0.031 728 7
Spectral bipartite frustration	b_K =	0.000 572 139
Controllability	C =	1,821

Plots

Fruchterman–Reingold graph drawing

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

Delaunay graph drawing

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

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.