node_measures {tidygraph}

Querying node measures

Description

These functions are a collection of node measures that do not really fall into the class of centrality measures. For lack of a better place they are collected under the ⁠node_*⁠ umbrella of functions.

Usage

node_eccentricity(mode = "out")

node_constraint(weights = NULL)

node_coreness(mode = "out")

node_diversity(weights)

node_efficiency(weights = NULL, directed = TRUE, mode = "all")

node_bridging_score()

node_effective_network_size()

node_connectivity_impact()

node_closeness_impact()

node_fareness_impact()

Arguments

mode

How edges are treated. In node_coreness() it chooses which kind of coreness measure to calculate. In node_efficiency() it defines how the local neighborhood is created

weights

The weights to use for each node during calculation

directed

Should the graph be treated as a directed graph if it is in fact directed

Value

A numeric vector of the same length as the number of nodes in the graph.

Functions

• node_eccentricity(): measure the maximum shortest path to all other nodes in the graph

• node_constraint(): measures Burts constraint of the node. See igraph::constraint()

• node_coreness(): measures the coreness of each node. See igraph::coreness()

• node_diversity(): measures the diversity of the node. See igraph::diversity()

• node_efficiency(): measures the local efficiency around each node. See igraph::local_efficiency()

• node_bridging_score(): measures Valente's Bridging measures for detecting structural bridges (influenceR)

• node_effective_network_size(): measures Burt's Effective Network Size indicating access to structural holes in the network (influenceR)

• node_connectivity_impact(): measures the impact on connectivity when removing the node (NetSwan)

• node_closeness_impact(): measures the impact on closeness when removing the node (NetSwan)

• node_fareness_impact(): measures the impact on fareness (distance between all node pairs) when removing the node (NetSwan)

Examples

# Calculate Burt's Constraint for each node
create_notable('meredith') %>%
  mutate(b_constraint = node_constraint())