These functions offer methods for summarising the closure in configurations in one-, two-, and three-mode networks:
network_reciprocity() measures reciprocity in a (usually directed) network.
node_reciprocity() measures nodes' reciprocity.
network_transitivity() measures transitivity in a network.
node_transitivity() measures nodes' transitivity.
network_equivalency() measures equivalence or reinforcement
in a (usually two-mode) network.
network_congruency() measures congruency across two two-mode networks.
network_reciprocity(.data, method = "default")
node_reciprocity(.data)
network_transitivity(.data)
node_transitivity(.data)
network_equivalency(.data)
network_congruency(.data, object2)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
For reciprocity, either default or ratio.
See ?igraph::reciprocity
Optionally, a second (two-mode) matrix, igraph, or tidygraph
For one-mode networks, shallow wrappers of igraph versions exist via
network_reciprocity and network_transitivity.
For two-mode networks, network_equivalency calculates the proportion of three-paths in the network
that are closed by fourth tie to establish a "shared four-cycle" structure.
For three-mode networks, network_congruency calculates the proportion of three-paths
spanning two two-mode networks that are closed by a fourth tie to establish a
"congruent four-cycle" structure.
The network_equivalency() function calculates the Robins and Alexander (2004)
clustering coefficient for two-mode networks.
Note that for weighted two-mode networks, the result is divided by the average tie weight.
Robins, Garry L, and Malcolm Alexander. 2004. Small worlds among interlocking directors: Network structure and distance in bipartite graphs. Computational & Mathematical Organization Theory 10(1): 69–94. doi:10.1023/B:CMOT.0000032580.12184.c0 .
Knoke, David, Mario Diani, James Hollway, and Dimitris C Christopoulos. 2021. Multimodal Political Networks. Cambridge University Press. Cambridge University Press. doi:10.1017/9781108985000
Other measures:
between_centrality,
close_centrality,
cohesion(),
degree_centrality,
eigenv_centrality,
features,
heterogeneity,
hierarchy,
holes,
net_diffusion,
node_diffusion,
periods
network_reciprocity(ison_southern_women)
#> [1] 1
node_reciprocity(to_unweighted(ison_networkers))
#> `Lin Freeman` `Doug White` `Ev Rogers` `Richard Alba` `Phipps Arabie`
#> 1 0.935 0.75 1 0.944 0.286
#> # ... with 27 more values from this nodeset unprinted. Use `print(..., n = Inf)` to print all values.
network_transitivity(ison_adolescents)
#> [1] 0.45
node_transitivity(ison_adolescents)
#> Betty Sue Alice Jane Dale Pam Carol Tina
#> 1 NaN 0.333 0.5 1 0.667 0.333 0 NaN
network_equivalency(ison_southern_women)
#> [1] 0.487