FilmTrust trust

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

Metadata

Code		`FT`
Internal name		`librec-filmtrust-trust`
Name		FilmTrust trust
Data source		https://www.librec.net/datasets.html
Availability		Dataset is available for download
Consistency check		Dataset passed all tests
Category		Online social network
Dataset timestamp		2011
Node meaning		User
Edge meaning		Trust
Network format		Unipartite, directed
Edge type		Unweighted, no multiple edges
Reciprocal		Contains reciprocal edges
Directed cycles		Contains directed cycles
Loops		Does not contain loops
Snapshot		Is a snapshot and likely to not contain all data

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	d_max =	118
Maximum outdegree	d⁺_max =	59
Maximum indegree	d⁻_max =	59
Average degree	d =	4.240 27
Fill	p =	0.002 428 57
Size of LCC	N =	610
Size of LSCC	N_s =	267
Relative size of LSCC	N^r_s =	0.305 492
Diameter	δ =	13
50-Percentile effective diameter	δ_0.5 =	4.379 61
90-Percentile effective diameter	δ_0.9 =	6.884 49
Median distance	δ_M =	5
Mean distance	δ_m =	5.010 09
Gini coefficient	G =	0.561 465
Balanced inequality ratio	P =	0.282 515
Outdegree balanced inequality ratio	P₊ =	0.302 752
Indegree balanced inequality ratio	P₋ =	0.306 530
Relative edge distribution entropy	H_er =	0.902 053
Power law exponent	γ =	2.523 87
Tail power law exponent	γ_t =	2.761 00
Tail power law exponent with p	γ₃ =	2.761 00
p-value	p =	0.614 000
Outdegree tail power law exponent with p	γ_3,o =	2.551 00
Outdegree p-value	p_o =	0.313 000
Indegree tail power law exponent with p	γ_3,i =	2.061 00
Indegree p-value	p_i =	0.000 00
Degree assortativity	ρ =	+0.078 230 2
Degree assortativity p-value	p_ρ =	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
Spectral separation	\|λ₁[A] / λ₂[A]\| =	1.615 58
Reciprocity	y =	0.587 156
Non-bipartivity	b_A =	0.438 526
Normalized non-bipartivity	b_N =	0.033 988 3
Algebraic non-bipartivity	χ =	0.059 906 8
Spectral bipartite frustration	b_K =	0.004 082 12
Controllability	C =	361
Relative controllability	C_r =	0.413 043

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.