View source: R/centralization.R

centr_betw | R Documentation |

See `centralize()`

for a summary of graph centralization.

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

`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. |

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 |

Other centralization related:
`centr_betw_tmax()`

,
`centr_clo_tmax()`

,
`centr_clo()`

,
`centr_degree_tmax()`

,
`centr_degree()`

,
`centr_eigen_tmax()`

,
`centr_eigen()`

,
`centralize()`

```
# 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
```

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