Function to determine the communities in a network using the Girvan-Newman algorithm. This function uses the cluster_edge_betweenness() function from the iGraph package, but creates a more user-friendly output that includes the names of the nodes.
Details
The GN-algorithm uses the edge betweenness to determine communities. Edge betweenness is the number of shortest paths between pairs of nodes running over that edge. The higher the edge betweenness, the more communities an edge connects. Therefore these are removed in this algorithm to detect communities.
References
Girvan, M and Newman, MEJ. 2002 Community structure in social and biological networks. Proceedings of the National Academy of Sciences of the United States of America 99(12): 7821–7826. DOI: https://doi.org/10.1073/pnas.122653799.
Newman, MEJ and Girvan, M. 2004 Finding and evaluating community structure in networks. Physical Review E 69(2): 026113. DOI: https://doi.org/10.1103/PhysRevE.69.026113.
Examples
hol_sim <- sim_table(hol_rom)
g_hol <- dendro_network(hol_sim)
gn_names(g_hol)
#> node com_name
#> 1 HOL_AAHOH GN_1
#> 2 HOL_KMBQH GN_1
#> 3 HOL_GKZBH GN_2
#> 4 HOL_KORHH GN_2
#> 5 HOL_LKBBH GN_2
#> 6 HOL_KBMBH GN_3
#> 7 HOL_LKSBH GN_3
#> 8 HOL_MBRUH GN_3
#> 9 HOL_MBUFH GN_3
#> 10 HOL_MRBRH GN_3
#> 11 HOL_PALZH GN_3
#> 12 HOL_TMB11H GN_3
#> 13 HOL_TRRBH GN_3
#> 14 HOL_TRRSH GN_3
#> 15 HOL_KORBH GN_4
#> 16 HOL_MB253H GN_4
#> 17 HOL_TRMB32H GN_4
#> 18 HOL_WEDEH GN_4
#> 19 HOL_WEDWH GN_4