Slashdot

This is the reply network of technology website Slashdot. Nodes are users and edges are replies. The edges are directed and start from the responding user. Edges are annotated with the timestamp of the reply.

Metadata

Code		`SD`
Internal name		`slashdot-threads`
Name		Slashdot
Availability		Dataset is available for download
Consistency check		Dataset passed all tests
Category		Communication network
Node meaning		User
Edge meaning		Reply
Network format		Unipartite, directed
Edge type		Unweighted, multiple edges
Temporal data		Edges are annotated with timestamps
Reciprocal		Contains reciprocal edges
Directed cycles		Contains directed cycles
Loops		Contains loops
Snapshot		Is a snapshot and likely to not contain all data

Statistics

Size	n =	51,083
Volume	m =	140,778
Unique edge count	m̿ =	131,175
Wedge count	s =	9,392,516
Claw count	z =	4,547,184,694
Cross count	x =	3,037,926,984,306
Triangle count	t =	18,937
Square count	q =	549,661
4-Tour count	T₄ =	42,200,498
Maximum degree	d_max =	3,357
Maximum outdegree	d⁺_max =	342
Maximum indegree	d⁻_max =	3,357
Average degree	d =	5.511 74
Fill	p =	5.026 88 × 10⁻⁵
Average edge multiplicity	m̃ =	1.073 21
Size of LCC	N =	51,083
Size of LSCC	N_s =	16,377
Relative size of LSCC	N^r_s =	0.320 596
Diameter	δ =	17
50-Percentile effective diameter	δ_0.5 =	4.073 23
90-Percentile effective diameter	δ_0.9 =	5.280 07
Median distance	δ_M =	5
Mean distance	δ_m =	4.589 05
Gini coefficient	G =	0.712 486
Relative edge distribution entropy	H_er =	0.881 606
Power law exponent	γ =	2.518 86
Tail power law exponent	γ_t =	1.911 00
Degree assortativity	ρ =	−0.034 675 3
Degree assortativity p-value	p_ρ =	0.000 00
In/outdegree correlation	ρ^± =	+0.716 637
Clustering coefficient	c =	0.006 048 54
Spectral norm	α =	91.502 9
Operator 2-norm	ν =	71.918 7
Cyclic eigenvalue	π =	40.475 8
Algebraic connectivity	a =	0.026 044 0
Spectral separation	\|λ₁[A] / λ₂[A]\| =	1.229 25
Reciprocity	y =	0.216 497
Non-bipartivity	b_A =	0.247 550
Normalized non-bipartivity	b_N =	0.014 353 1
Spectral bipartite frustration	b_K =	0.001 428 07
Controllability	C =	33,852
Relative controllability	C_r =	0.390 000

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

Degree assortativity

Zipf plot

Hop distribution

In/outdegree scatter plot

Edge weight/multiplicity distribution

Clustering coefficient distribution

Average neighbor degree distribution

Temporal distribution

Temporal hop distribution

Diameter/density evolution

SynGraphy

Inter-event distribution

Node-level inter-event distribution

Matrix decompositions plots

Downloads

Data as TSV (906,851 bytes)
KONECT extraction code (GitHub)

References

[1]	Jérôme Kunegis. KONECT – The Koblenz Network Collection. In Proc. Int. Conf. on World Wide Web Companion, pages 1343–1350, 2013. [ http ]
[2]	Vicenç Gómez, Andreas Kaltenbrunner, and Vicente López. Statistical analysis of the social network and discussion threads in Slashdot. In Proc. Int. World Wide Web Conf., pages 645–654, 2008.