Twitter user–item
This is the bipartite network consisting of Twitter users and the URLs they
mentioned in their postings. Left nodes represent users and right nodes
represent URLs. An edge shows that an URL was mentioned by a user in a tweet.
Metadata
Statistics
Size  n =  9,374,206

Left size  n_{1} =  244,537

Right size  n_{2} =  9,129,669

Volume  m =  12,656,613

Unique edge count  m̿ =  10,214,177

Wedge count  s =  708,995,210

Claw count  z =  1,155,590,474,676

Cross count  x =  5,291,997,635,686,715

Square count  q =  53,711,135

4Tour count  T_{4} =  3,286,104,890

Maximum degree  d_{max} =  24,106

Maximum left degree  d_{1max} =  855

Maximum right degree  d_{2max} =  24,106

Average degree  d =  2.700 31

Average left degree  d_{1} =  51.757 5

Average right degree  d_{2} =  1.386 32

Fill  p =  4.575 13 × 10^{−6}

Average edge multiplicity  m̃ =  1.239 12

Size of LCC  N =  7,488,524

Diameter  δ =  30

50Percentile effective diameter  δ_{0.5} =  7.524 28

90Percentile effective diameter  δ_{0.9} =  9.761 17

Mean distance  δ_{m} =  8.134 08

Gini coefficient  G =  0.623 814

Balanced inequality ratio  P =  0.263 288

Left balanced inequality ratio  P_{1} =  0.285 079

Right balanced inequality ratio  P_{2} =  0.418 375

Relative edge distribution entropy  H_{er} =  0.906 108

Power law exponent  γ =  8.945 62

Tail power law exponent  γ_{t} =  3.261 00

Degree assortativity  ρ =  −0.042 714 3

Degree assortativity pvalue  p_{ρ} =  0.000 00

Spectral norm  α =  1,713.76

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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, YuRu 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.
