Closeness centrality - delegates to igraph::closeness. On a disconnected graph, plain closeness is ill-defined across components (nodes in tiny components score spuriously high, distorting leader selection); we fall back to harmonic centrality, the robust generalisation that handles unreachable pairs (Boldi & Vigna 2014). Note the two are NOT identical even on a connected graph – closeness inverts the mean distance, harmonic averages the inverse distances – so on disconnected inputs (e.g. PolBlogs, and the frequently-disconnected induced subgraphs of variant 2) the selected leader may differ from a per-component closeness; this is a deliberate robustness choice, recorded here so benchmark results are interpreted accordingly.
Source:R/lcda_grasp.R
centrality_closeness.RdCloseness centrality - delegates to igraph::closeness. On a disconnected graph, plain closeness is ill-defined across components (nodes in tiny components score spuriously high, distorting leader selection); we fall back to harmonic centrality, the robust generalisation that handles unreachable pairs (Boldi & Vigna 2014). Note the two are NOT identical even on a connected graph – closeness inverts the mean distance, harmonic averages the inverse distances – so on disconnected inputs (e.g. PolBlogs, and the frequently-disconnected induced subgraphs of variant 2) the selected leader may differ from a per-component closeness; this is a deliberate robustness choice, recorded here so benchmark results are interpreted accordingly.