MovieLens user–tag

This bipartite network shows the tagging behaviour of 72,000 users of Left nodes are users and right nodes are tags. An edge connects a user with a tag he applied to a movie.


Internal namemovielens-10m_ut
NameMovieLens user–tag
Data source
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Interaction network
Node meaningUser, tag
Edge meaningAssignment
Network formatBipartite, undirected
Edge typeUnweighted, multiple edges
Temporal data Edges are annotated with timestamps


Size n =20,537
Left size n1 =4,009
Right size n2 =16,528
Volume m =95,580
Unique edge count m̿ =43,760
Wedge count s =8,091,394
Claw count z =3,409,576,286
Cross count x =1,454,031,072,304
Square count q =1,580,737
4-Tour count T4 =45,103,872
Maximum degree dmax =6,012
Maximum left degree d1max =6,012
Maximum right degree d2max =641
Average degree d =9.308 08
Average left degree d1 =23.841 4
Average right degree d2 =5.782 91
Fill p =0.000 660 421
Average edge multiplicity m̃ =2.184 19
Size of LCC N =19,665
Diameter δ =14
50-Percentile effective diameter δ0.5 =3.767 09
90-Percentile effective diameter δ0.9 =5.515 21
Median distance δM =4
Mean distance δm =4.414 66
Gini coefficient G =0.828 724
Balanced inequality ratio P =0.152 767
Left balanced inequality ratio P1 =0.125 811
Right balanced inequality ratio P2 =0.198 347
Relative edge distribution entropy Her =0.841 697
Power law exponent γ =2.755 53
Tail power law exponent γt =2.001 00
Tail power law exponent with p γ3 =2.001 00
p-value p =0.001 000 00
Left tail power law exponent with p γ3,1 =2.061 00
Left p-value p1 =0.058 000 0
Right tail power law exponent with p γ3,2 =2.161 00
Right p-value p2 =0.103 000
Degree assortativity ρ =−0.180 095
Degree assortativity p-value pρ =1.072 44 × 10−315
Spectral norm α =640.915
Algebraic connectivity a =0.027 834 6
Spectral separation 1[A] / λ2[A]| =1.023 22
Controllability C =14,029
Relative controllability Cr =0.683 109


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

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] GroupLens Research. MovieLens data sets., October 2006.