member_equivalence: Memberships in equivalent classes

In netrics: Many Ways to Measure and Classify Membership for Networks, Nodes, and Ties

Memberships in equivalent classes

Description

These functions combine an appropriate ⁠node_x_*()⁠ function together with methods for calculating the hierarchical clusters provided by a certain distance calculation.

• node_in_equivalence() assigns nodes membership based on their equivalence with respective to some motif/class. The following functions call this function, together with an appropriate motif.

• node_in_structural() assigns nodes membership based on their having equivalent ties to the same other nodes.

• node_in_regular() assigns nodes membership based on their having equivalent patterns of ties.

• node_in_automorphic() assigns nodes membership based on their having equivalent distances to other nodes.

A plot() method exists for investigating the dendrogram of the hierarchical cluster and showing the returned cluster assignment.

Usage

node_in_equivalence(
  .data,
  motif,
  k = c("silhouette", "elbow", "strict"),
  cluster = c("hierarchical", "concor", "cosine"),
  distance = c("euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski"),
  Kmax = 8L
)

node_in_structural(
  .data,
  k = c("silhouette", "elbow", "strict"),
  cluster = c("hierarchical", "concor", "cosine"),
  distance = c("euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski"),
  Kmax = 8L
)

node_in_regular(
  .data,
  k = c("silhouette", "elbow", "strict"),
  cluster = c("hierarchical", "concor", "cosine"),
  distance = c("euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski"),
  Kmax = 8L
)

node_in_automorphic(
  .data,
  k = c("silhouette", "elbow", "strict"),
  cluster = c("hierarchical", "concor", "cosine"),
  distance = c("euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski"),
  Kmax = 8L
)

Arguments

.data	A network object of class mnet, igraph, tbl_graph, network, or similar. For more information on the standard coercion possible, see manynet::as_tidygraph().
motif	A matrix returned by a ⁠node_x_*()⁠ function.
k	Typically a character string indicating which method should be used to select the number of clusters to return. By default "silhouette", other options include "elbow" and "strict". "strict" returns classes with members only when strictly equivalent. "silhouette" and "elbow" select classes based on the distance between clusters or between nodes within a cluster. Fewer, identifiable letters, e.g. "e" for elbow, is sufficient. Alternatively, if k is passed an integer, e.g. k = 3, then all selection routines are skipped in favour of this number of clusters.
cluster	Character string indicating whether clusters should be clustered hierarchically ("hierarchical") or through convergence of correlations ("concor"). Fewer, identifiable letters, e.g. "c" for CONCOR, is sufficient.
distance	Character string indicating which distance metric to pass on to stats::dist. By default "euclidean", but other options include "maximum", "manhattan", "canberra", "binary", and "minkowski". Fewer, identifiable letters, e.g. "e" for Euclidean, is sufficient.
Kmax	Integer indicating the maximum number of (k) clusters to evaluate. Ignored when k = "strict" or a discrete number is given for k.

Value

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.

Source

https://github.com/aslez/concoR

See Also

Other memberships: member_brokerage, member_cliques, member_community, member_community_hier, member_community_non, member_components, member_core, member_diffusion

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_core, member_diffusion, motif_brokerage_node, motif_exposure, motif_node, motif_path

Examples

(nse <- node_in_structural(ison_algebra))
(nre <- node_in_regular(ison_southern_women,
  cluster = "concor"))
if(require("sna", quietly = TRUE)){
(nae <- node_in_automorphic(ison_southern_women,
  k = "elbow"))
}

netrics documentation built on July 24, 2026, 5:07 p.m.