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

CodeSD
Internal nameslashdot-threads
NameSlashdot
AvailabilityDataset is available for download
Consistency checkDataset passed all tests
Category
Communication network
Node meaningUser
Edge meaningReply
Network formatUnipartite, directed
Edge typeUnweighted, multiple edges
Temporal data Edges are annotated with timestamps
ReciprocalContains reciprocal edges
Directed cyclesContains directed cycles
LoopsContains 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
Loop count l =989
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 dmax =3,357
Maximum outdegree d+max =342
Maximum indegree dmax =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 Ns =16,377
Relative size of LSCC Nrs =0.320 596
Diameter δ =17
50-Percentile effective diameter δ0.5 =4.073 23
90-Percentile effective diameter δ0.9 =5.280 07
Median distance δM =5
Mean distance δm =4.589 05
Gini coefficient G =0.712 486
Balanced inequality ratio P =0.208 655
Outdegree balanced inequality ratio P+ =0.263 599
Indegree balanced inequality ratio P =0.219 786
Relative edge distribution entropy Her =0.881 606
Power law exponent γ =2.518 86
Tail power law exponent γt =1.911 00
Tail power law exponent with p γ3 =1.911 00
p-value p =0.000 00
Outdegree tail power law exponent with p γ3,o =2.371 00
Outdegree p-value po =0.000 00
Indegree tail power law exponent with p γ3,i =2.061 00
Indegree p-value pi =0.000 00
Degree assortativity ρ =−0.034 675 3
Degree assortativity p-value pρ =5.857 49 × 10−63
In/outdegree correlation ρ± =+0.716 637
Clustering coefficient c =0.006 048 54
Directed clustering coefficient c± =0.009 869 28
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 1[A] / λ2[A]| =1.229 25
Reciprocity y =0.216 497
Non-bipartivity bA =0.247 550
Normalized non-bipartivity bN =0.014 353 1
Algebraic non-bipartivity χ =0.026 251 3
Spectral bipartite frustration bK =0.001 428 07
Controllability C =33,852
Relative controllability Cr =0.662 686

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

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

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.