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You may also take a look at the source code.
The networks in this dataset can be loaded directly from graph-tool with:(and likewise for the other networks available.)import graph_tool.all as gt g = gt.collection.ns["mag_history_coauthor/max-25-bip"]
A hypergraph representing collaborations among authors listed in the Microsoft Academic Graph (MAG), derived from papers with the "History" tag as of 3 Sept. 2017. Each node represents an author, and each publication is represented by a simplex (a set of nodes, i.e., a hyperedge), timestamped by the year of publication. Simplices are restricted to at most 25 authors. In addition to the hypergraph, a weighted projection of the same network is available.1
Name | Nodes | Edges | $\left<k\right>$ | $\sigma_k$ | $\lambda_h$ | $\tau$ | $r$ | $c$ | $\oslash$ | $S$ | Kind | Mode | NPs | EPs | gt | GraphML | GML | csv |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
max-25-bip | 2,847,387 | 2,367,289 | 1.66 | 5.22 | 32.80 | 23855.08 | -0.01 | 0.00 | 66 | 0.27 | Undirected | Bipartite | label is_simplex | time | 15.8 MiB | 27.5 MiB | 23.3 MiB | 30.1 MiB |
max-25-proj | 1,034,875 | 1,365,815 | 2.64 | 10.41 | 66.30 | 13821.63 | 0.52 | 0.46 | 32 | 0.21 | Undirected | Unipartite | label | time | 10.5 MiB | 16.5 MiB | 14.9 MiB | 16.7 MiB |
full-bip | 2,848,023 | 2,398,702 | 1.68 | 5.33 | 32.80 | 23855.16 | -0.01 | 0.00 | 66 | 0.28 | Undirected | Bipartite | label is_simplex | time | 16.0 MiB | 27.8 MiB | 23.6 MiB | 30.4 MiB |
full-proj | 1,034,875 | 2,984,794 | 5.77 | 37.66 | 923.00 | 52378.04 | 0.84 | 0.86 | 32 | 0.23 | Undirected | Unipartite | label | time | 11.0 MiB | 20.8 MiB | 18.9 MiB | 21.0 MiB |