returns the eigenvector associated with the dominant eigenvalue from the adjacency matrix.

`eigen_centrality_signed(g, scale = TRUE)`

## Arguments

- g
igraph object with a sign edge attribute.

- scale
Logical scalar, whether to scale the result to have a maximum score of one. If no scaling is used then the result vector is the same as returned by `eigen()`

.

## Value

centrality scores as numeric vector.

## Details

Note that, with negative values, the adjacency matrix may not have a dominant eigenvalue.
This means it is not clear which eigenvector should be used. In addition it is possible for the adjacency matrix to have repeated eigenvalues and hence multiple linearly independent eigenvectors. In this case certain centralities can be arbitrarily assigned. The function returns an error if this is the case.

## References

Bonacich, P. and Lloyd, P. (2004). "Calculating Status with Negative Relations." *Social Networks* 26 (4): 331–38.

Everett, M. and Borgatti, S.P. (2014). "Networks Containing Negative Ties." *Social Networks* 38: 111–20.

## Examples

```
library(igraph)
data("tribes")
eigen_centrality_signed(tribes)
#> [1] 1.00000000 0.88879594 0.71609511 0.36818769 0.74303157 0.95454966
#> [7] 0.76017717 0.67100494 0.21063522 0.23890028 0.69639725 0.91352983
#> [13] 0.23390770 0.05855799 0.91193923 0.98724909
```