# node_measures

##### Querying node measures

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

```
# NOT RUN {
# Calculate Burt's Constraint for each node
create_notable('meredith') %>%
mutate(b_constraint = node_constraint())
# }
```

*Documentation reproduced from package tidygraph, version 1.1.2, License: MIT + file LICENSE*