hierarchy: Graph theoretic dimensions of hierarchy

In migraph: Multimodal Network Analysis and More

Graph theoretic dimensions of hierarchy

Description

Graph theoretic dimensions of hierarchy

Usage

network_connectedness(.data)

network_efficiency(.data)

network_upperbound(.data)

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

Functions

• network_connectedness(): Returns the proportion of dyads in the network that are reachable, otherwise degree to which network is a single component

• network_efficiency(): Returns the Krackhardt efficiency score

• network_upperbound(): Returns the Krackhardt (least) upper bound score

References

Krackhardt, David. 1994. Graph theoretical dimensions of informal organizations. In Carley and Prietula (eds) Computational Organizational Theory, Hillsdale, NJ: Lawrence Erlbaum Associates. Pp. 89-111.

Everett, Martin, and David Krackhardt. 2012. “A second look at Krackhardt's graph theoretical dimensions of informal organizations.” Social Networks, 34: 159-163. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.socnet.2011.10.006")}

See Also

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

Examples

network_connectedness(ison_networkers)
1 - network_reciprocity(ison_networkers)
network_efficiency(ison_networkers)
network_upperbound(ison_networkers)

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