Bridging Centrality

Bridging centrality (Hwang et al. 2008) is the product of betweenness \(B(v)\) and the bridging coefficient, which compares the inverse degree of a node with the inverse degrees of its neighbors: $$BrC(v) = B(v) \frac{1/k_v}{\sum_{u \in N(v)} 1/k_u}.$$ High values mark nodes that lie on many shortest paths and connect densely linked regions.

Usage

centrality_bridging(x, ...)

Arguments

x

Network input accepted by centrality.

...

Further arguments to centrality, such as directed and normalized.

Value

A named numeric vector with one score per node, in input node order.

Details

The betweenness factor reads edge weights as path lengths and follows the edge direction of a directed network. weighted = FALSE uses hop counts, and invert_weights has no effect. The degrees are total degrees, and on a directed network a reciprocated neighbor enters the sum twice. An isolated node scores 0.

References

Hwang, W., Kim, T., Ramanathan, M., & Zhang, A. (2008). Bridging centrality: Graph mining from element level to group level. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 336-344). doi:10.1145/1401890.1401934 .

See also

centrality_local_bridging, centrality_betweenness, centrality.

Examples

centrality_bridging(regulation_net)
#>    Explore       Plan    Monitor      Adapt    Reflect    Discuss Synthesize 
#>  0.8254717  1.7697431  1.6321244  2.2556391  1.5037594  0.1272727  2.7029703 
#>   Evaluate     Create      Share 
#>  0.8064000  1.6490486  1.6912752