These functions return values relating to how connected a network is and the number of nodes or edges to remove that would increase fragmentation.
net_by_cohesion() measures the minimum number of nodes to remove
from the network needed to increase the number of components.
net_by_toughness() measures the number of nodes that would need to be
removed from a network to increase its number of components.
net_by_adhesion() measures the minimum number of ties to remove
from the network needed to increase the number of components.
net_by_strength() measures the number of ties that would need to be
removed from a network to increase its number of components.
net_by_cohesion(.data)
net_by_adhesion(.data)
net_by_strength(.data)
net_by_toughness(.data)A network object of class stocnet, igraph, tbl_graph, network, or similar.
Internally any of these will be coerced to an efficient implementation.
For more information on possible coercions, see e.g. manynet::as_stocnet().
A network_measure numeric score.
The object also carries the measure it computed, the range its values
can fall within, and whether and how those values were normalized.
These are shown as a one-line header when the object is printed.
Where a measure offers a choice between several ways of counting the
same thing, it also carries the variant it used.
All can be retrieved with attr().
White, Douglas R and Frank Harary. 2001. "The Cohesiveness of Blocks In Social Networks: Node Connectivity and Conditional Density." Sociological Methodology 31(1): 305-59. doi:10.1111/0081-1750.00098
Other cohesion:
mark_triangles,
measure_breadth,
measure_cohesion,
motif_net,
motif_node
Other measures:
measure_assort_net,
measure_assort_node,
measure_breadth,
measure_broker_node,
measure_broker_tie,
measure_brokerage,
measure_central_between,
measure_central_close,
measure_central_degree,
measure_central_eigen,
measure_central_tie_between,
measure_central_tie_close,
measure_central_tie_degree,
measure_central_tie_eigen,
measure_closure,
measure_closure_node,
measure_cohesion,
measure_core,
measure_diffusion_infection,
measure_diffusion_net,
measure_diffusion_node,
measure_diverse_net,
measure_diverse_node,
measure_features,
measure_fit,
measure_hierarchy,
measure_periods
net_by_cohesion(fict_marvel)
#> # Node connectivity [0, Inf)
#> [1] 2
net_by_cohesion(to_giant(fict_marvel))
#> # Node connectivity [0, Inf)
#> [1] 2
net_by_adhesion(fict_marvel)
#> # Tie connectivity [0, Inf)
#> [1] 2
net_by_adhesion(to_giant(fict_marvel))
#> # Tie connectivity [0, Inf)
#> [1] 2
net_by_strength(ison_adolescents)
#> # Strength [0, Inf)
#> [1] 0.5
net_by_toughness(ison_adolescents)
#> # Toughness [0, Inf)
#> [1] 0.5