swan_closeness measures the change in the sum of the inverse of distances between all node pairs
when excluding that node.#'
Details
swan_closeness measures the impact of a node's removal by computing the change in
the sum of inverse distances between all node pairs.
The code is an adaptation from the NetSwan package that was archived on CRAN.
References
Lhomme S. (2015). Analyse spatiale de la structure des réseaux techniques dans un contexte de risques. Cybergeo: European Journal of Geography.
Examples
library(igraph)
# Example graph (electrical network structure)
elec <- matrix(ncol = 2, byrow = TRUE, c(
11,1, 11,10, 1,2, 2,3, 2,9,
3,4, 3,8, 4,5, 5,6, 5,7,
6,7, 7,8, 8,9, 9,10
))
gra <- graph_from_edgelist(elec, directed = FALSE)
# Compute swan_closeness
f2 <- swan_closeness(gra)
# Compare with betweenness centrality
bet <- betweenness(gra)
reg <- lm(bet ~ f2)
summary(reg)
#>
#> Call:
#> lm(formula = bet ~ f2)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -1.6235 -0.3692 0.1222 0.4552 1.2889
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) -0.2541 0.4486 -0.566 0.585
#> f2 -6.0531 0.3058 -19.791 9.96e-09 ***
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual standard error: 0.836 on 9 degrees of freedom
#> Multiple R-squared: 0.9775, Adjusted R-squared: 0.975
#> F-statistic: 391.7 on 1 and 9 DF, p-value: 9.959e-09
#>