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.

node_eccentricity(mode = "out") node_constraint(weights = NULL) node_coreness(mode = "out") node_diversity(weights) node_bridging_score() node_effective_network_size() node_connectivity_impact() node_closeness_impact() node_fareness_impact()

mode | The way edges should be followed in the case of directed graphs. |
---|---|

weights | The weights to use for each node during calculation |

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

`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`

)

# Calculate Burt's Constraint for each node create_notable('meredith') %>% mutate(b_constraint = node_constraint())#> # A tbl_graph: 70 nodes and 140 edges #> # #> # An undirected simple graph with 1 component #> # #> # Node Data: 70 x 1 (active) #> b_constraint #> <dbl> #> 1 0.25 #> 2 0.25 #> 3 0.25 #> 4 0.25 #> 5 0.25 #> 6 0.25 #> # … with 64 more rows #> # #> # Edge Data: 140 x 2 #> from to #> <int> <int> #> 1 1 5 #> 2 1 6 #> 3 1 7 #> # … with 137 more rows