Filmtipset comments

This is the bipartite network of users commenting on movies, from the Swedish movie rating website The nodes of the network are the users and the movie. Each link connects a user with a movie, and denote a single comment by that users on that movie. Multiple link between the same user–movie pair are allowed. Each link is annotated with the timestamp of the comment.


Internal namefilmtipset_comment
NameFilmtipset comments
Data source
AvailabilityDataset is not available for download
Consistency checkDataset passed all tests
Interaction network
Dataset timestamp 2010
Node meaningUser, movie
Edge meaningComment
Network formatBipartite, undirected
Edge typeUnweighted, multiple edges
Temporal data Edges are annotated with timestamps


Size n =75,360
Left size n1 =29,530
Right size n2 =45,830
Volume m =1,266,753
Unique edge count m̿ =1,204,831
Wedge count s =493,367,139
Claw count z =204,725,098,142
Cross count x =136,282,597,862,835
Square count q =2,724,858,975
4-Tour count T4 =23,774,988,546
Maximum degree dmax =5,659
Maximum left degree d1max =5,659
Maximum right degree d2max =2,252
Average degree d =33.618 7
Average left degree d1 =42.897 2
Average right degree d2 =27.640 3
Fill p =0.000 890 252
Average edge multiplicity m̃ =1.051 39
Size of LCC N =75,194
Diameter δ =9
50-Percentile effective diameter δ0.5 =3.297 78
90-Percentile effective diameter δ0.9 =4.305 01
Median distance δM =4
Mean distance δm =3.749 21
Gini coefficient G =0.803 195
Balanced inequality ratio P =0.171 261
Left balanced inequality ratio P1 =0.169 335
Right balanced inequality ratio P2 =0.144 105
Power law exponent γ =1.578 01
Tail power law exponent γt =1.581 00
Tail power law exponent with p γ3 =1.581 00
p-value p =0.000 00
Left tail power law exponent with p γ3,1 =2.041 00
Left p-value p1 =0.000 00
Right tail power law exponent with p γ3,2 =1.631 00
Right p-value p2 =0.000 00
Degree assortativity ρ =−0.186 575
Degree assortativity p-value pρ =0.000 00
Algebraic connectivity a =0.196 326
Controllability C =40,256
Relative controllability Cr =0.534 183


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

Edge weight/multiplicity 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] Alan Said, Ernesto W. De Luca, and Sahin Albayrak. How social relationships affect user similarities. In Proc. IUI Workshop on Soc. Recomm. Syst., 2010.