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KONECT > Networks > Twitter (ICWSM)

Twitter (ICWSM)

About this network

This is the directed network containing information about who follows whom on Twitter. Nodes represent users and an edge shows that the left user follows the right one.

Network info

CodeWs
Category Social
Data source http://www.public.asu.edu/~mdechoud/datasets.html
Vertex type User
Edge type Follow
FormatDirected: Edges are directed Directed
Edge weightsUnweighted: Simple edges Unweighted
Size465,017 vertices (users)
Volume834,797 edges (follows)
Average degree (overall)3.5904 edges / vertex
Fill3.8605 × 10–6 edges / vertex2
Maximum degree678 edges
Reciprocity0.301%
Size of LCC465,017 vertices (network is connected)
Size of LSCC1,726 vertices
Wedge count187,988,707
Claw count28,887,087,190
Triangle count38,389
Square count21,828,900
4-tour count928,253,108
Power law exponent (estimated) with dmin2.4710 (dmin = 1)
Gini coefficient69.5%
Relative edge distribution entropy82.3%
Assortativity–0.87772
Clustering coefficient0.0613%
Diameter8 edges
90-percentile effective diameter4.96 edges
Mean shortest path length4.59 edges
Spectral norm81.600
Algebraic connectivity0.0073170
Degree distribution of the Twitter (ICWSM) network
Degree distribution
Outdegree distribution of the Twitter (ICWSM) network
Outdegree distribution
Indegree distribution of the Twitter (ICWSM) network
Indegree distribution
Degree distribution of the Twitter (ICWSM) network
Degree distribution
Outdegree distribution of the Twitter (ICWSM) network
Outdegree distribution
Indegree distribution of the Twitter (ICWSM) network
Indegree distribution
Degree distribution of the Twitter (ICWSM) network
Degree distribution
Outdegree distribution of the Twitter (ICWSM) network
Outdegree distribution
Indegree distribution of the Twitter (ICWSM) network
Indegree distribution
Clustering coefficient distribution of the Twitter (ICWSM) network
Clustering coefficient distribution
Distance distribution of the Twitter (ICWSM) network
Distance distribution
Distance distribution on a logistic scale of the Twitter (ICWSM) network
Distance distribution on a logistic scale
Top-k eigenvalues of A of the Twitter (ICWSM) network
Top-k eigenvalues of A
Top-k eigenvalues of N of the Twitter (ICWSM) network
Top-k eigenvalues of N
Top-k eigenvalues of L of the Twitter (ICWSM) network
Top-k eigenvalues of L
Spectral distribution of the eigenvalues of A of the Twitter (ICWSM) network
Spectral distribution of the eigenvalues of A
Spectral distribution of the eigenvalues of N of the Twitter (ICWSM) network
Spectral distribution of the eigenvalues of N
Spectral distribution of the eigenvalues of L of the Twitter (ICWSM) network
Spectral distribution of the eigenvalues of L
Cumulative spectral distribution of A of the Twitter (ICWSM) network
Cumulative spectral distribution of A
Cumulative spectral distribution of N of the Twitter (ICWSM) network
Cumulative spectral distribution of N
Cumulative spectral distribution of L of the Twitter (ICWSM) network
Cumulative spectral distribution of L
Complex eigenvalues of the asymmetric adjacency matrix of the Twitter (ICWSM) network
Complex eigenvalues of the asymmetric adjacency matrix

Downloads

TSV file:downloadmunmun_twitter_social.tar.bz2 (2.33 MiB)
Extraction code:downloadmunmun.tar.bz2 (29.59 KiB)
RDF:download RDFmunmun_twitter_social.n3.bz2 (2.88 MiB)

References

[1] Twitter (icwsm) network dataset -- KONECT, October 2016. [ 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.

BibTeX