# centr_betw

From igraph v1.0.0
by Gabor Csardi

##### Centralize a graph according to the betweenness of vertices

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 passed to the
`betweenness`

function. - 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.

##### See Also

Other centralization related: `centr_betw_tmax`

,
`centralization.betweenness.tmax`

;
`centr_clo_tmax`

,
`centralization.closeness.tmax`

;
`centr_clo`

,
`centralization.closeness`

;
`centr_degree_tmax`

,
`centralization.degree.tmax`

;
`centr_degree`

,
`centralization.degree`

;
`centr_eigen_tmax`

,
`centralization.evcent.tmax`

;
`centr_eigen`

,
`centralization.evcent`

;
`centralization`

, `centralize`

,
`centralize.scores`

##### 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
```

*Documentation reproduced from package igraph, version 1.0.0, License: GPL (>= 2)*

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