Table 2 Characteristics of datasets, \(|\mathbf{V} |\) is the number of nodes, \(|\mathbf{E} |\) is the number of edges, \(\overline{\mathbf{p }}\) is the mean of the edge probabilities, \(\rho = 2|E|/(|V| (|V|-1))\) is graph density and \(\overline{D} = 2|E|/|V|\) is average degree (Lee et al. 2010)
From: Probabilistic network sparsification with ego betweenness
Dataset | |V| | |E| | \(\overline{{p}}\) | \(\rho\) | \(\overline{D}\) |
|---|---|---|---|---|---|
Brain network | 89 | 3916 | 0.526 | 1 | 88 |
Enron | 805 | 3956 | 0.173 | 0.012 | 9.83 |
FriendFeed | 9894 | 172,567 | 0.11 | 0.002 | 34.88 |
ER (high \(\rho\)) | 1000 | 449,550 | 0.49 | 0.9 | 899.1 |
ER (medium \(\rho\)) | 1000 | 249,750 | 0.5 | 0.5 | 499.5 |
ER (low \(\rho\)) | 1000 | 49,950 | 0.53 | 0.1 | 99.9 |
FF (high \(\rho\)) | 1000 | 449,550 | 0.51 | 0.9 | 899.1 |
FF (medium \(\rho\)) | 1000 | 249,750 | 0.49 | 0.5 | 499.5 |
FF (low \(\rho\)) | 1000 | 49,950 | 0.48 | 0.1 | 99.9 |