These functions offer methods for summarising the closure in configurations in one-, two-, and three-mode networks.
network_reciprocity(object, method = "default")
node_reciprocity(object)
network_transitivity(object)
node_transitivity(object)
network_equivalency(object)
network_congruency(object, object2)A one-mode or two-mode matrix, igraph, or tidygraph
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.
network_reciprocity(): Calculate reciprocity in a (usually directed) network
node_reciprocity(): Calculate nodes' reciprocity
network_transitivity(): Calculate transitivity in a network
node_transitivity(): Calculate nodes' transitivity
network_equivalency(): Calculate equivalence or reinforcement
in a (usually two-mode) network
network_congruency(): Calculate congruency across two two-mode networks
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:
centralisation,
centrality,
cohesion(),
diversity,
features,
holes,
tie_centrality
network_reciprocity(ison_southern_women)
#> [1] 1
node_reciprocity(to_unweighted(ison_networkers))
#> `LIN FREEMAN` DOUG W…¹ EV RO…² RICHA…³ PHIPP…⁴ CAROL…⁵ GARY …⁶ RUSS …⁷ JOHN …⁸
#> 1 0.935 0.75 1 0.944 0.286 0.8 1 0.8 0.818
#> # ... with 23 more from this nodeset in the vector.
network_transitivity(ison_adolescents)
#> [1] 0.45
node_transitivity(ison_adolescents)
#> V1 V2 V3 V4 V5 V6 V7 V8
#> 1 NaN 0.333 0.5 1 0.667 0.333 0 NaN
network_equivalency(ison_southern_women)
#> [1] 0.487