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Community detection using the Girvan-Newman algorithm

Source: R/gn_names.R
gn_names.Rd

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.

Usage

gn_names(g)

Arguments

g

input graph or network that is used for community detection

Value

the names of the nodes in the various communities

Details

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