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

## Description

See `centralize` for a summary of graph centralization.

## Usage

 ```1 2 3 4 5 6``` ```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

 ```1 2 3 4 5 6``` ```# 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 ```

### Example output

```Attaching package: 'igraph'

The following objects are masked from 'package:stats':

decompose, spectrum

The following object is masked from 'package:base':

union

 0.1588275
 0.4222048
 0.2493544
 0.9453363
```

igraph documentation built on March 19, 2020, 5:13 p.m.