FilmTrust trust

This is the user–user trust network of the FilmTrust project.

Metadata

CodeFT
Internal namelibrec-filmtrust-trust
NameFilmTrust trust
Data sourcehttps://www.librec.net/datasets.html
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Category
Online social network
Dataset timestamp 2011
Node meaningUser
Edge meaningTrust
Network formatUnipartite, directed
Edge typeUnweighted, no multiple edges
ReciprocalContains reciprocal edges
Directed cyclesContains directed cycles
LoopsDoes not contain loops
Completeness Is incomplete

Statistics

Size n =874
Volume m =1,853
Loop count l =0
Wedge count s =11,730
Claw count z =511,885
Cross count x =10,641,250
Triangle count t =749
Square count q =4,370
4-Tour count T4 =84,498
Maximum degree dmax =118
Maximum outdegree d+max =59
Maximum indegree dmax =59
Average degree d =4.240 27
Fill p =0.002 428 57
Size of LCC N =610
Size of LSCC Ns =267
Relative size of LSCC Nrs =0.305 492
Diameter δ =13
50-Percentile effective diameter δ0.5 =4.379 61
90-Percentile effective diameter δ0.9 =6.884 49
Median distance δM =5
Mean distance δm =5.010 09
Gini coefficient G =0.561 465
Relative edge distribution entropy Her =0.902 053
Power law exponent γ =2.523 87
Tail power law exponent γt =2.761 00
Degree assortativity ρ =+0.078 230 2
Degree assortativity p-value pρ =6.149 80 × 10−5
In/outdegree correlation ρ± =+0.514 988
Clustering coefficient c =0.191 560
Directed clustering coefficient c± =0.191 274
Spectral norm α =24.251 9
Operator 2-norm ν =12.582 8
Cyclic eigenvalue π =11.668 1
Algebraic connectivity a =0.055 237 0
Reciprocity y =0.587 156
Non-bipartivity bA =0.438 526
Normalized non-bipartivity bN =0.033 988 3
Algebraic non-bipartivity χ =0.059 906 8
Spectral bipartite frustration bK =0.004 082 12

Plots

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

In/outdegree scatter plot

Clustering coefficient distribution

Average neighbor degree 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] Guobing Guo, Jia Zhang, and Neil Yorke-Smith. A novel Bayesian similarity measure for recommender systems. In Proc. Int. Joint Conf. on Artif. Intell., pages 2619–2625, 2013.