# centr_degree: Centralize a graph according to the degrees of vertices In igraph: Network Analysis and Visualization

 centr_degree R Documentation

## Centralize a graph according to the degrees of vertices

### Description

See `centralize()` for a summary of graph centralization.

### Usage

``````centr_degree(
graph,
mode = c("all", "out", "in", "total"),
loops = TRUE,
normalized = TRUE
)
``````

### Arguments

 `graph` The input graph. `mode` This is the same as the `mode` argument of `degree()`. `loops` Logical scalar, whether to consider loops edges when calculating the degree. `normalized` Logical scalar. Whether to normalize the graph level centrality score by dividing by the theoretical maximum.

### Value

A named list with the following components:

 `res` The node-level centrality scores. `centralization` The graph level centrality index. `theoretical_max` The maximum theoretical graph level centralization score for a graph with the given number of vertices, using the same parameters. If the `normalized` argument was `TRUE`, then the result was divided by this number.

Other centralization related: `centr_betw_tmax()`, `centr_betw()`, `centr_clo_tmax()`, `centr_clo()`, `centr_degree_tmax()`, `centr_eigen_tmax()`, `centr_eigen()`, `centralize()`

### Examples

``````# A BA graph is quite centralized
g <- sample_pa(1000, m = 4)
centr_degree(g)\$centralization
centr_clo(g, mode = "all")\$centralization
centr_betw(g, directed = FALSE)\$centralization
centr_eigen(g, directed = FALSE)\$centralization
``````

igraph documentation built on Aug. 10, 2023, 9:08 a.m.