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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["dblp_cite"]

dblp_cite — DBLP citations (2014)


Citations among papers contained in the DBLP computer science bibliography. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. This snapshot from May 2014.1

  1. Description obtained from the ICON project. 

Informational Citation Unweighted
  • M. Ley, "The DBLP computer science bibliography: Evolution, research issues, perspectives." Proc. of the 9th Int. Symposium on String Processing and Information Retrieval (SPIRE), 1-10 (2002), https://doi.org/10.1007/3-540-45735-6_1 [@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
dblp_cite 12,590 49,759 3.95 16.87 38.11 20.56 -0.05 0.06 10 0.99 Directed Unipartite weight time 275 KiB 418 KiB 400 KiB 342 KiB
None drawing