Twitter (MPI)
This asymmetric network contains Twitter follow data based on a snapshot taken
in 2009. A node represents a user. A directed edge indicates that a user
follows another user.
Metadata
Statistics
Size | n = | 52,579,682
|
Volume | m = | 1,963,263,821
|
Loop count | l = | 313
|
Wedge count | s = | 177,464,933,477,000
|
Triangle count | t = | 55,428,217,664
|
Maximum degree | dmax = | 3,691,240
|
Maximum outdegree | d+max = | 779,958
|
Maximum indegree | d−max = | 3,503,656
|
Average degree | d = | 74.677 7
|
Size of LCC | N = | 52,515,193
|
Diameter | δ = | 18
|
50-Percentile effective diameter | δ0.5 = | 3.151 81
|
90-Percentile effective diameter | δ0.9 = | 4.052 51
|
Mean distance | δm = | 3.615 64
|
Clustering coefficient | c = | 0.000 937 000
|
Operator 2-norm | ν = | 6,971.10
|
Reciprocity | y = | 0.355 691
|
Non-bipartivity | bA = | 0.380 728
|
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]
|
Meeyoung Cha, Hamed Haddadi, Fabricio Benevenuto, and Krishna P. Gummadi.
Measuring user influence in Twitter: The million follower fallacy.
In Proc. Int. Conf. on Weblogs and Soc. Media, pages 10–17,
2010.
|