Table 2 |
|||
| Results on Facebook network samples | |||
| Algorithm | No. communities | Network modularity | Time (s) |
| BFS (8.21M vertices, 12.58M edges) | |||
| FNCA | 50,156 | 0.6867 | 5.97⋅104 |
| LPA | 48,750 | 0.6963 | 2.27⋅104 |
| Uniform (7.69M vertices, 7.84M edges) | |||
| FNCA | 40,700 | 0.9650 | 3.77⋅104 |
| LPA | 48,022 | 0.9749 | 2.32⋅104 |
This table summarizes performance and results of the two chosen community detection algorithms (i.e., FNCA and LPA) applied to the samples we collected from Facebook.
Ferrara EPJ Data Science 2012 1:9 doi:10.1186/epjds9
