Filmtipset ratings

This is the bipartite rating graph of, a Swedish movie rating website. Nodes of the network are users and movie, and edges denote individual ratings by a user of a movie. The weight of an edge is the rating on a scale from 1 (bad movie) to 5 (good movie).


Internal namefilmtipset_rating
NameFilmtipset ratings
Data source
AvailabilityDataset is not available for download
Consistency checkDataset passed all tests
Rating network
Dataset timestamp 2010
Node meaningUser, movie
Edge meaningRating
Network formatBipartite, undirected
Edge typeRatings, multiple edges
Temporal data Edges are annotated with timestamps


Size n =144,671
Left size n1 =80,482
Right size n2 =64,189
Volume m =19,554,219
Unique edge count m̿ =19,553,591
Wedge count s =113,150,077,280
Claw count z =823,402,527,757,975
Cross count x =7,047,301,388,153,398,272
Square count q =8,728,909,858,170
Maximum degree dmax =65,245
Maximum left degree d1max =13,651
Maximum right degree d2max =65,245
Average degree d =270.327
Average left degree d1 =242.964
Average right degree d2 =304.635
Fill p =0.003 785 01
Average edge multiplicity m̃ =1.000 03
Size of LCC N =144,653
Diameter δ =7
50-Percentile effective diameter δ0.5 =2.305 10
90-Percentile effective diameter δ0.9 =3.522 78
Median distance δM =3
Mean distance δm =2.843 58
Gini coefficient G =0.766 918
Balanced inequality ratio P =0.197 423
Left balanced inequality ratio P1 =0.219 938
Right balanced inequality ratio P2 =0.083 228 2
Relative edge distribution entropy Her =0.846 060
Power law exponent γ =1.286 53
Tail power law exponent γt =1.531 00
Degree assortativity ρ =−0.303 551
Degree assortativity p-value pρ =0.000 00
Spectral norm α =7,653.24
Negativity ζ =0.487 063


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

Item rating evolution

Edge weight/multiplicity distribution

Temporal distribution

Diameter/density evolution

Signed temporal distribution

Inter-event distribution

Node-level inter-event distribution



[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.