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twitter_15m — Twitter 15-M movement (2011)

Description

Directed network of follower relationships among Twitter users who took part in the online activity around the 15-M (Indignados) protest movement in Spain, collected from 25 April to 25 May 2011. The messages were collected by Cierzo Development Ltd. and include only messages in Spanish related to the movement, identified by a set of hashtags. The network includes users who sent at least one message on the topic, or who were mentioned by a user who did, and contains only the follower relationships among these users (87,569 nodes). The data were made available by Y. Moreno and J. Borge-Holthoefer.

Edges follow the direction of the information flow: an edge $i \to j$ indicates that user $j$ follows user $i$.

The upstream data also contain the time, hashtags and mentions of the collected messages, which are not included in the network. The node properties id and name hold the (meaningless) node labels of the upstream Pajek file, and the edge property weight is always 1.

Tags
Social Online Unweighted Metadata
Added
2020-09-26
Citation
  • S. González-Bailón, et al. "The dynamics of protest recruitment through an online network." Scientific Reports 1, 197 (2011) 10.1038/srep00197 Sci-Hub
Upstream URL OK
http://www.plexmath.eu/?page_id=320
Networks
Tip: hover over a column header for a description.
Column legend
$\left<k\right>$
Mean degree
$\sigma_k$
Standard deviation of the degrees
$\lambda_h$
Largest eigenvalue of the Hashimoto (non-backtracking) matrix
$\tau$
Random walk mixing time
$r$
Degree assortativity
$c$
Global clustering coefficient
$\oslash$
(Pseudo-) diameter
$S$
Relative size of the largest component
NPs
Node properties
EPs
Edge properties
Name Nodes Edges $\left<k\right>$ $\sigma_k$ $\lambda_h$ $\tau$ $r$ $c$ $\oslash$ $S$ Kind Mode NPs EPs gt GraphML GML csv
twitter_15m 87,569 6,030,459 68.87 471.29 666.53 3.30 -0.13 0.04 6 0.98 Directed Unipartite id name weight 10.6 MiB 14.4 MiB 23.1 MiB 20.9 MiB
Ridiculograms*
* These are automatically generated force-directed visualizations, and can be quite meaningless for networks both big and small. They should not be taken seriously as sources of scientific insight. See here for a discussion.