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

 centr_betw R Documentation

## Centralize a graph according to the betweenness of vertices

### Description

See `centralize` for a summary of graph centralization.

### Usage

```centr_betw(graph, directed = TRUE, nobigint = TRUE, normalized = TRUE)
```

### Arguments

 `graph` The input graph. `directed` logical scalar, whether to use directed shortest paths for calculating betweenness. `nobigint` Logical scalar, whether to use big integers for the betweenness calculation. This argument is deprecated in igraph 1.3 and will be removed in igraph 1.4. `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_clo_tmax()`, `centr_clo()`, `centr_degree_tmax()`, `centr_degree()`, `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 July 20, 2022, 1:07 a.m.