Marks of nodes based on degree properties

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_isolate() marks nodes that are isolates, with neither incoming nor outgoing ties.

• node_is_pendant() marks nodes that are pendants, with exactly one incoming or outgoing tie.

• node_is_universal() identifies whether nodes are adjacent to all other nodes in the network.

node_is_isolate(.data)

node_is_pendant(.data)

node_is_universal(.data)

Arguments

.data

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().

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.

Cognitive social structures

A cognitive social structure records each node's report of the ties in the whole network, in a by column that names who reported each tie. Counting every report as a tie of its own would count each tie once for every perceiver who reports it. So the functions here first combine the reports into the locally aggregated structure of Krackhardt (1987), with the intersection rule: a tie exists if both of its ends report it, and a message says so. A tie that names no reporter is kept as it is.

A tie-level function still returns one value for each report, so that the result can be added back to the network it was given. Each report takes the value of the tie that it reports. A report of a tie that is not in the aggregated structure takes NA, or FALSE for a mark. tie_is_random() is the exception, and draws among the reports.

To combine the reports in a different way, do this before the function, e.g. with manynet::to_aggregated(over = "by").

Krackhardt, David. 1987. "Cognitive social structures". Social Networks 9(2): 109-134. doi:10.1016/0378-8733(87)90009-8

Universal/dominating node

A universal node is adjacent to all other nodes in the network. It is also sometimes called the dominating vertex because it represents a one-element dominating set. A network with a universal node is called a cone, and its universal node is called the apex of the cone. A classic example of a cone is a star graph, but friendship, wheel, and threshold graphs are also cones.

See also

Other degree: measure_central_degree, measure_central_tie_degree, measure_centralisation_degree

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

Other nodal: mark_core, 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_modular, member_community_partition, member_community_spread, member_components, member_core, member_diffusion, member_equivalence, motif_brokerage_node, motif_clique, motif_composition, motif_exposure, motif_node, motif_path

Examples

node_is_isolate(ison_brandes)
#>   N01   N02   N03   N04   N05   N06   N07   N08   N09   N10   N11  
#> 1 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
node_is_universal(create_star(11))
#>   V1    V2    V3    V4    V5    V6    V7    V8    V9    V10   V11  
#> 1 TRUE  FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE