The is the directed network of a small subset of posts to other user's wall on Facebook. The nodes of the network are Facebook users, and each directed edge represents one post, linking the users writing a post to the users whose wall the post is written on. Since users may write multiple posts on a wall, the network allows multiple edges connecting a single node pair. Since users may write on their own wall, the network contains loops.


Internal namefacebook-wosn-wall
Data sourcehttp://socialnetworks.mpi-sws.org/data-wosn2009.html
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Communication network
Dataset timestamp 2009
Node meaningUser
Edge meaningWall post
Network formatUnipartite, directed
Edge typeUnweighted, multiple edges
Temporal data Edges are annotated with timestamps
ReciprocalContains reciprocal edges
Directed cyclesContains directed cycles
LoopsContains loops
Snapshot Is a snapshot and likely to not contain all data


Size n =46,952
Volume m =876,993
Unique edge count m̿ =274,086
Loop count l =21,451
Wedge count s =4,331,017
Claw count z =221,524,187
Cross count x =6,265,197,027
Triangle count t =122,852
Square count q =1,265,222
4-Tour count T4 =27,812,668
Maximum degree dmax =2,696
Maximum outdegree d+max =1,430
Maximum indegree dmax =1,428
Average degree d =37.357 0
Average edge multiplicity m̃ =3.199 70
Size of LCC N =43,953
Size of LSCC Ns =30,793
Relative size of LSCC Nrs =0.655 840
Diameter δ =18
50-Percentile effective diameter δ0.5 =5.192 22
90-Percentile effective diameter δ0.9 =6.835 71
Median distance δM =6
Mean distance δm =5.711 18
Gini coefficient G =0.734 791
Balanced inequality ratio P =0.207 820
Outdegree balanced inequality ratio P+ =0.219 194
Indegree balanced inequality ratio P =0.213 269
Relative edge distribution entropy Her =0.938 798
Power law exponent γ =1.704 87
Tail power law exponent γt =4.431 00
Tail power law exponent with p γ3 =4.431 00
p-value p =0.015 000 0
Outdegree tail power law exponent with p γ3,o =4.751 00
Outdegree p-value po =0.000 00
Indegree tail power law exponent with p γ3,i =3.691 00
Indegree p-value pi =0.000 00
Degree assortativity ρ =+0.219 968
Degree assortativity p-value pρ =0.000 00
Clustering coefficient c =0.085 096 9
Directed clustering coefficient c± =0.082 923 0
Spectral norm α =1,717.63
Operator 2-norm ν =904.598
Cyclic eigenvalue π =856.606
Algebraic connectivity a =0.037 776 7
Spectral separation 1[A] / λ2[A]| =1.011 73
Reciprocity y =0.624 862
Non-bipartivity bA =0.011 597 7
Normalized non-bipartivity bN =0.029 854 5
Spectral bipartite frustration bK =0.001 767 33


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

Double Laplacian graph drawing

Delaunay graph drawing

In/outdegree scatter plot

Edge weight/multiplicity 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.