Twitter user–tag
This is a bipartite network consisting of Twitter users and tags they mentioned
in their postings. Left nodes represent users and right nodes represent tags.
An edge shows that a tag was used by a user in a tweet.
Metadata
Statistics
Size | n = | 705,632
|
Left size | n1 = | 175,214
|
Right size | n2 = | 530,418
|
Volume | m = | 4,664,605
|
Unique edge count | m̿ = | 1,890,661
|
Wedge count | s = | 1,006,768,611
|
Claw count | z = | 3,620,991,361,242
|
Cross count | x = | 14,011,028,889,674,202
|
Square count | q = | 206,508,691
|
4-Tour count | T4 = | 5,682,999,878
|
Maximum degree | dmax = | 90,362
|
Maximum left degree | d1max = | 2,431
|
Maximum right degree | d2max = | 90,362
|
Average degree | d = | 13.221 1
|
Average left degree | d1 = | 26.622 3
|
Average right degree | d2 = | 8.794 21
|
Fill | p = | 2.034 35 × 10−5
|
Average edge multiplicity | m̃ = | 2.467 18
|
Size of LCC | N = | 690,906
|
Diameter | δ = | 16
|
50-Percentile effective diameter | δ0.5 = | 5.022 02
|
90-Percentile effective diameter | δ0.9 = | 5.893 74
|
Median distance | δM = | 6
|
Mean distance | δm = | 5.319 70
|
Gini coefficient | G = | 0.842 861
|
Balanced inequality ratio | P = | 0.149 222
|
Left balanced inequality ratio | P1 = | 0.236 392
|
Right balanced inequality ratio | P2 = | 0.135 109
|
Relative edge distribution entropy | Her = | 0.882 745
|
Power law exponent | γ = | 2.460 48
|
Tail power law exponent | γt = | 2.601 00
|
Degree assortativity | ρ = | −0.098 655 9
|
Degree assortativity p-value | pρ = | 0.000 00
|
Spectral norm | α = | 2,216.48
|
Algebraic connectivity | a = | 0.003 077 89
|
Spectral separation | |λ1[A] / λ2[A]| = | 1.010 44
|
Controllability | C = | 437,932
|
Relative controllability | Cr = | 0.620 624
|
Plots
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]
|
Munmun De Choudhury, Yu-Ru Lin, Hari Sundaram, K. Selçuk Candan, Lexing Xie,
and Aisling Kelliher.
How does the data sampling strategy impact the discovery of
information diffusion in social media?
In ICWSM, pages 34–41, 2010.
|