mark_select_node: Marking nodes based on measures

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

Marking nodes based on measures

Description

These functions return logical vectors the length of the nodes in a network identifying which hold certain properties or positions in the network.

• node_is_random() marks one or more nodes at random.

• node_is_max() and node_is_min() are more generally useful for converting the results from some node measure into a mark-class object. They can be particularly useful for highlighting which node or nodes are key because they minimise or, more often, maximise some measure.

Usage

node_is_random(.data, select = 1)

node_is_max(node_measure, ranks = 1)

node_is_min(node_measure, ranks = 1)

node_is_mean(node_measure, ranks = 1)

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().
select	Number of elements to select (as TRUE).
node_measure	An object created by a node_ measure.
ranks	The number of ranks of max or min to return. For example, ranks = 3 will return TRUE for nodes with scores equal to any of the top (or, for node_is_min(), bottom) three scores. By default, ranks = 1.

Value

A node_mark logical vector the length of the nodes in the network, giving either TRUE or FALSE for each node depending on whether the condition is matched.

See Also

Other selection: mark_select_tie

Other marks: mark_core, mark_degree, mark_diff, mark_dyads, mark_nodes, mark_select_tie, mark_ties, mark_triangles

Other nodal: mark_core, mark_degree, mark_diff, mark_nodes, 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, member_equivalence, motif_brokerage_node, motif_exposure, motif_node, motif_path

Examples

node_is_random(ison_brandes, 2)
node_is_max(node_by_degree(ison_brandes))
node_is_min(node_by_degree(ison_brandes))
node_is_mean(node_by_degree(ison_brandes))

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