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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_2009"]

twitter_2009 — Twitter graph (2009)


A large (possibly complete) snapshot of Twitter in 2009, represented as an anonymized network of accounts and their follow links.1

  1. Description obtained from the ICON project. 

Social Online Unweighted
  • M. Cha, H. Haddadi, F. Benevenuto, and K. P. Gummadi, "Measuring User Influence in Twitter: The Million Follower Fallacy" Proc. Internat. AAAI Conf. on Weblogs and Social Media (ICWSM), 10-17 (2010)., https://doi.org/10.1145/2897659.2897663 [@sci-hub]
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_2009 52,579,682 1,963,263,821 37.34 2698.38 7004.31 4799.30 -0.07 0.00 18 1.00 Directed Unipartite name 5.041 GiB 9.348 GiB 9.344 GiB 7.887 GiB