node_in_core() categorizes nodes into two or more core/periphery
categories based on their coreness.
A network object of class stocnet, igraph, tbl_graph, network, or similar.
Internally any of these will be coerced to an efficient implementation.
For more information on possible coercions, see e.g. manynet::as_stocnet().
Number of categories to create. Must be at least 2 and at most the number of nodes in the network. Default is 3.
Which method to use to split the coreness scores into the categories. One of "bins" (equal-width bins), "quantiles" (quantile-based bins), or "kmeans" (k-means clustering); see method_split for what each does. Default is "bins".
Which method to use to calculate nodes' coreness. One of "correlation", "rich", "transition", or "hub"; see method_coreness for what each does. By default NULL, which uses "rich" for a weighted, directed, or two-mode network, since it is the only method that reads those properties directly, and "correlation" otherwise.
One of "all" (the default), "out", "in", or "both". For a directed network, "out" scores nodes on the ties they send and "in" on the ties they receive, while "both" returns the four categories described below. Ignored for undirected and two-mode networks.
Deprecated. The former spelling of split.
Still accepted, but warns; please use split instead.
A node_member character vector the length of the nodes in the network,
of group memberships "A", "B", etc for each node.
If the network is labelled,
then the assignments will be labelled with the nodes' names.
This function categorizes nodes based on their coreness into a specified number of groups. The groups are labeled as "Core", "Semi-core", "Semi-periphery", and "Periphery" depending on the number of groups specified. The categorization can be done using different methods: equal-width bins, quantile-based bins, or k-means clustering.
In a directed network a node can be core in whom it reaches and
peripheral in who reaches it, which one core and one periphery cannot
express. direction = "both" therefore returns the four categories that
Elliott and colleagues distinguish:
"Core" for nodes in both the out-core and the in-core,
"Sender" for nodes in the out-core only,
"Receiver" for nodes in the in-core only,
"Periphery" for nodes in neither.
This uses coreness_hub(), so groups and split do not apply.
Wallerstein, Immanuel. 1974. "Dependence in an Interdependent World: The Limited Possibilities of Transformation Within the Capitalist World Economy." African Studies Review, 17(1), 1-26. doi:10.2307/523574
Elliott, Andrew, Angus Chiu, Marya Bazzi, Gesine Reinert, and Mihai Cucuringu. 2020. "Core-periphery structure in directed networks". Proceedings of the Royal Society A 476(2241): 20190783. doi:10.1098/rspa.2019.0783
Other core-periphery:
mark_core,
measure_core
Other memberships:
member_brokerage,
member_cliques,
member_community,
member_community_hier,
member_community_non,
member_components,
member_diffusion,
member_equivalence
Other nodal:
mark_core,
mark_degree,
mark_diff,
mark_nodes,
mark_select_node,
measure_assort_node,
measure_broker_node,
measure_brokerage,
measure_central_between,
measure_central_close,
measure_central_degree,
measure_central_eigen,
measure_closure_node,
measure_core,
measure_diffusion_node,
measure_diverse_node,
member_brokerage,
member_cliques,
member_community,
member_community_hier,
member_community_non,
member_components,
member_diffusion,
member_equivalence,
motif_brokerage_node,
motif_clique,
motif_composition,
motif_exposure,
motif_node,
motif_path
node_in_core(ison_adolescents)
#> 3 groups
#> Betty Sue Alice Jane Dale Pam Carol Tina
#> 1 Periphery Semi-periphery Core Semi-periphery Semi-periphery Semi… Peri… Peri…
node_in_core(ison_networkers, direction = "both")
#> 3 groups
#> `Lin Freeman` `Doug White` `Ev Rogers` `Richard Alba` `Phipps Arabie`
#> 1 Core Core Core Core Core
#> # ... and 27 more values from this nodeset. Use `print_all(...)` to print all values.