Constraint

Everett and Borgatti specification of the constraint measure for binary matrices

Usage

eb_constraint(A, ego = NULL, digraph = FALSE, weighted = FALSE)

Arguments

A

A symmetric matrix object

ego

Name of ego in the matrix

digraph

Whether the matrix is directed or undirected

weighted

Whether the matrix is weighted or not

Value

This function returns term 1, 2 and 3, the normalization and the maximum value of the specification of Everett and Borgatti (2020), and the constraint of Burt (1992).

References

Burt, R.S., 1992. Structural Holes: the Social Structure of Competition. Harvard University Press, Cambridge.

Everett, M.G. and Borgatti, S., 2020. Unpacking Burt's constraint measure. Social Networks 62, pp. 50-57. doi: https://doi.org/10.1016/j.socnet.2020.02.001

Author

Alejandro Espinosa-Rada

Examples

A <- matrix(c(
  0, 1, 1, 0, 0, 1,
  1, 0, 1, 0, 0, 1,
  1, 1, 0, 0, 0, 1,
  0, 0, 0, 0, 1, 1,
  0, 0, 0, 1, 0, 1,
  1, 1, 1, 1, 1, 0
), ncol = 6, byrow = TRUE)

rownames(A) <- letters[1:nrow(A)]
colnames(A) <- letters[1:ncol(A)]
eb_constraint(A, ego = "f")
#> $results
#>   term1 term2 term3 constraint normalization
#> f   0.2  0.24 0.073      0.513         0.699
#> 
#> $maximum
#>     f 
#> 0.648 
#>