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Percolation Centrality

Source: R/centrality.R
centrality_percolation.Rd

Importance for spreading processes using node states. Each node has a state (0-1) representing how activated it is. When all states are equal, equivalent to betweenness.

Usage

centrality_percolation(x, states = NULL, ...)

Arguments

x

Network input (matrix, igraph, network, cograph_network, tna object).

states

Named numeric vector of node states (0-1). Default NULL (all nodes get state 1).

...

Additional arguments passed to centrality (e.g., weighted, directed).

Value

Named numeric vector of percolation centrality values.

See also

centrality for computing multiple measures at once, centrality_betweenness which this generalizes.

Examples

adj <- matrix(c(0, 1, 1, 1, 0, 1, 1, 1, 0), 3, 3)
rownames(adj) <- colnames(adj) <- c("A", "B", "C")
centrality_percolation(adj)
#> A B C 
#> 0 0 0 
centrality_percolation(adj, states = c(A = 0.8, B = 0.2, C = 0.5))
#> A B C 
#> 0 0 0