between_centrality: Measures of betweenness-like centrality and centralisation

In migraph: Multimodal Network Analysis and More

Measures of betweenness-like centrality and centralisation

Description

Measures of betweenness-like centrality and centralisation

Usage

node_betweenness(.data, normalized = TRUE, cutoff = NULL)

tie_betweenness(.data, normalized = TRUE)

network_betweenness(
  .data,
  normalized = TRUE,
  direction = c("all", "out", "in")
)

Arguments

.data	An object of a {manynet}-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
normalized	Logical scalar, whether the centrality scores are normalized. Different denominators are used depending on whether the object is one-mode or two-mode, the type of centrality, and other arguments.
cutoff	The maximum path length to consider when calculating betweenness. If negative or NULL (the default), there's no limit to the path lengths considered.
direction	Character string, “out” bases the measure on outgoing ties, “in” on incoming ties, and "all" on either/the sum of the two. For two-mode networks, "all" uses as numerator the sum of differences between the maximum centrality score for the mode against all other centrality scores in the network, whereas "in" uses as numerator the sum of differences between the maximum centrality score for the mode against only the centrality scores of the other nodes in that mode.

Value

A numeric vector giving the betweenness centrality measure of each node.

Functions

• node_betweenness(): Calculate the betweenness centralities of nodes in a network

• tie_betweenness(): Calculate number of shortest paths going through a tie

• network_betweenness(): Calculate the betweenness centralization for a network

See Also

Other measures: close_centrality, closure, cohesion(), degree_centrality, eigenv_centrality, features, heterogeneity, hierarchy, holes

Other centrality: close_centrality, degree_centrality, eigenv_centrality

Examples

node_betweenness(mpn_elite_mex)
node_betweenness(ison_southern_women)
(tb <- tie_betweenness(ison_adolescents))
plot(tb)
#ison_adolescents %>% mutate_ties(weight = tb) %>% 
#   autographr()
network_betweenness(ison_southern_women, direction = "in")

migraph documentation built on Nov. 2, 2023, 5:47 p.m.