These functions return values or vectors relating to how connected a network is and the number of nodes or edges to remove that would increase fragmentation.

network_density(object)

network_components(object)

network_cohesion(object)

network_diameter(object)

network_length(object)

## Arguments

object

An object of a migraph-consistent class:

• matrix (adjacency or incidence) from {base} R

• edgelist, a data frame from {base} R or tibble from {tibble}

• igraph, from the {igraph} package

• network, from the {network} package

• tbl_graph, from the {tidygraph} package

## Functions

• network_density(): summarises the ratio of ties to the number of possible ties.

• network_components(): Returns number of (strong) components in the network. To get the 'weak' components of a directed graph, please use to_undirected() first.

• network_cohesion(): Returns the minimum number of nodes to remove from the network needed to increase the number of components.

• network_adhesion(): Returns the minimum number of edges needed to remove from the network to increase the number of components.

• network_diameter(): Returns the maximum path length in the network.

• network_length(): Returns the average path length in the network.

## References

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.

Other measures: centralisation, centrality, closure, diversity, features, holes, tie_centrality

## Examples

network_density(mpn_elite_mex)
#> [1] 0.197
#> [1] 0.164
network_cohesion(ison_marvel_relationships)
#> [1] 0
network_cohesion(to_giant(ison_marvel_relationships))
#> [1] 5