R: Closeness centrality of vertices

closeness {igraph} | R Documentation

## Closeness centrality of vertices

### Description

Closeness centrality measures how many steps is required to access every other vertex from a given vertex.

### Usage

    closeness(
      graph,
      vids = V(graph),
      mode = c("out", "in", "all", "total"),
      weights = NULL,
      normalized = FALSE
    )

    estimate_closeness(
      graph,
      vids = V(graph),
      mode = c("out", "in", "all", "total"),
      cutoff,
      weights = NULL,
      normalized = FALSE
    )

### Arguments

`graph` | The graph to analyze.
`vids` | The vertices for which closeness will be calculated.
`mode` | Character string, defined the types of the paths used for measuring the distance in directed graphs. “in” measures the paths to a vertex, “out” measures paths from a vertex, all uses undirected paths. This argument is ignored for undirected graphs.
`weights` | Optional positive weight vector for calculating weighted closeness. If the graph has a `weight` edge attribute, then this is used by default. Weights are used for calculating weighted shortest paths, so they are interpreted as distances.
`normalized` | Logical scalar, whether to calculate the normalized closeness. Normalization is performed by multiplying the raw closeness by n-1, where n is the number of vertices in the graph.
`cutoff` | The maximum path length to consider when calculating the betweenness. If zero or negative then there is no such limit.

### Details

The closeness centrality of a vertex is defined by the inverse of the average length of the shortest paths to/from all the other vertices in the graph:

1/sum( d(v,i), i != v)

If there is no (directed) path between vertex `v` and `i`, then the total number of vertices is used in the formula instead of the path length.

`estimate_closeness` only considers paths of length `cutoff` or smaller, this can be run for larger graphs, as the running time is not quadratic (if `cutoff` is small). If `cutoff` is zero or negative then the function calculates the exact closeness scores.

### Value

Numeric vector with the closeness values of all the vertices in `v`.

### Author(s)

Gabor Csardi csardi.gabor@gmail.com

### References

Freeman, L.C. (1979). Centrality in Social Networks I: Conceptual Clarification. Social Networks, 1, 215-239.

### See Also

`betweenness`, `degree`

### Examples

    g <- make_ring(10)
    g2 <- make_star(10)
    closeness(g)
    closeness(g2, mode="in")
    closeness(g2, mode="out")
    closeness(g2, mode="all")

[Package igraph version 1.2.10 Index]