Filmtipset friendships

This is the social network from, a Swedish movie rating website. Nodes in the network are users of the website and links denote friendship. The network is undirected and simple, i.e. each node pair can only be connected by a single link.


Internal namefilmtipset_friend
NameFilmtipset friendships
Data source
AvailabilityDataset is not available for download
Consistency checkDataset passed all tests
Online social network
Dataset timestamp 2010
Node meaningUser
Edge meaningFriendship
Network formatUnipartite, undirected
Edge typeUnweighted, no multiple edges
LoopsDoes not contain loops


Size n =39,199
Volume m =87,415
Loop count l =0
Wedge count s =2,566,266
Claw count z =666,823,593
Cross count x =223,106,248,436
Triangle count t =70,151
Square count q =403,278
4-Tour count T4 =13,666,118
Maximum degree dmax =1,479
Average degree d =4.460 06
Fill p =0.000 113 783
Size of LCC N =36,475
Diameter δ =17
50-Percentile effective diameter δ0.5 =5.340 08
90-Percentile effective diameter δ0.9 =7.168 34
Median distance δM =6
Mean distance δm =5.874 44
Gini coefficient G =0.542 476
Balanced inequality ratio P =0.293 760
Relative edge distribution entropy Her =0.943 025
Power law exponent γ =2.020 98
Tail power law exponent γt =3.661 00
Tail power law exponent with p γ3 =3.661 00
p-value p =0.012 000 0
Degree assortativity ρ =−0.013 372 5
Degree assortativity p-value pρ =2.249 88 × 10−8
Clustering coefficient c =0.082 007 5
Spectral norm α =40.379 6
Algebraic connectivity a =0.021 471 7
Spectral separation 1[A] / λ2[A]| =1.067 36
Non-bipartivity bA =0.063 112 0
Normalized non-bipartivity bN =0.026 814 6
Algebraic non-bipartivity χ =0.049 669 9
Spectral bipartite frustration bK =0.002 652 64
Controllability C =8,305
Relative controllability Cr =0.211 868


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

Double Laplacian graph drawing

Delaunay graph drawing

Clustering coefficient distribution

Average neighbor degree 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] Alan Said, Ernesto W. De Luca, and Sahin Albayrak. How social relationships affect user similarities. In Proc. IUI Workshop on Soc. Recomm. Syst., 2010.