R: Querying node measures

node_measures {tidygraph} | R Documentation

## 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 = NULL)

    node_bridging_score()

    node_effective_network_size()

    node_connectivity_impact()

    node_closeness_impact()

    node_fareness_impact()

### Arguments

`mode` | The way edges should be followed in the case of directed graphs.
`weights` | The weights to use for each node during calculation

### 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_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())

[Package tidygraph version 1.1.2 Index]