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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)

Description

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. 

Tags
Social Online Unweighted
Citation
  • 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
http://twitter.mpi-sws.org/
Networks
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 9.219 GiB 7.887 GiB