Flixster

This is the social network of Flixster, a movie rating site on which people can meet others with a similar movie taste. The network is undirected and unweighted.

Metadata

CodeFX
Internal nameflixster
NameFlixster
Data sourcehttp://socialcomputing.asu.edu/datasets/Flixster
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Category
Online social network
Node meaningUser
Edge meaningFriendship
Network formatUnipartite, undirected
Edge typeUnweighted, no multiple edges
LoopsDoes not contain loops

Statistics

Size n =2,523,386
Volume m =7,918,801
Loop count l =0
Wedge count s =1,735,571,393
Claw count z =370,427,745,071
Cross count x =74,755,363,821,014
Triangle count t =7,897,122
Square count q =454,368,595
4-Tour count T4 =10,593,071,934
Maximum degree dmax =1,474
Average degree d =6.276 33
Fill p =2.487 27 × 10−6
Size of LCC N =2,523,386
Diameter δ =8
50-Percentile effective diameter δ0.5 =4.331 57
90-Percentile effective diameter δ0.9 =5.380 07
Mean distance δm =4.815 72
Gini coefficient G =0.775 506
Balanced inequality ratio P =0.177 717
Relative edge distribution entropy Her =0.863 745
Power law exponent γ =2.594 10
Tail power law exponent γt =1.911 00
Degree assortativity ρ =−0.321 231
Degree assortativity p-value pρ =0.000 00
Clustering coefficient c =0.013 650 5
Spectral norm α =148.325
Non-bipartivity bA =0.332 584
Normalized non-bipartivity bN =0.010 436 1
Spectral bipartite frustration bK =0.000 802 782

Plots

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

Hop distribution

Clustering coefficient distribution

SynGraphy

Matrix decompositions plots

Downloads

References

[1] Jérôme Kunegis. KONECT – The Koblenz Network Collection. In Proc. Int. Conf. on World Wide Web Companion, pages 1343–1350, 2013. [ http ]
[2] R. Zafarani and H. Liu. Social computing data repository at ASU, 2009. [ http ]