migraph (version 0.12.1)

tie_centrality: Measures of tie centrality

Description

Measures of tie centrality

Usage

tie_degree(object, normalized = TRUE)
tie_closeness(object, normalized = TRUE)
tie_betweenness(object, normalized = TRUE)
tie_eigenvector(object, normalized = TRUE)

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

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.

Functions

• tie_degree(): Calculate the degree centrality of edges in a network

• tie_closeness(): Calculate the closeness of each edge to each other edge in the network.

• tie_betweenness(): Calculate number of shortest paths going through an edge

• tie_eigenvector(): Calculate the eigenvector centrality of edges in a network

See Also

Other measures: centralisation, centrality, closure, cohesion(), diversity, features, holes

Examples

tie_degree(ison_adolescents)
(ec <- tie_closeness(ison_adolescents))
plot(ec)
ison_adolescents %>% 
  activate(edges) %>% mutate(weight = ec) %>% 
  autographr()
(tb <- tie_betweenness(ison_adolescents))
plot(tb)
ison_adolescents %>% 
  activate(edges) %>% mutate(weight = tb) %>% 
  autographr()
tie_eigenvector(ison_adolescents)