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You may also take a look at the source code.
The network in this dataset can be loaded directly from graph-tool with:
import graph_tool.all as gt
g = gt.collection.ns["twitter_sample"]

twitter_sample — Twitter sample (2014)


A sample of the Twitter follower network in 2012, obtained by crawling follower links outward breadth- or depth-first from an arbitrary set of seed profiles. Nodes are twitter accounts, and edges represent the directed following relationship.1

  1. Description obtained from the ICON project. 

Social Online Unweighted
  • D. Kagan, M. Fire, and Y. Elovici, "Unsupervised Anomalous Vertices Detection Utilizing Link Prediction Algorithms", Preprint, arXiv:1610.07525 (2017), https://arxiv.org/abs/1610.07525
Upstream URL OK
Tip: hover your mouse over a table header to obtain a legend.
Name Nodes Edges $\left<k\right>$ $\sigma_k$ $\lambda_h$ $\tau$ $r$ $c$ $\oslash$ $S$ Kind Mode NPs EPs gt GraphML GML csv
twitter_sample 5,384,162 16,011,444 2.97 47.65 431.87 399.06 -0.21 0.02 9 1.00 Directed Unipartite 40.1 MiB 72.1 MiB 70.2 MiB 65.8 MiB