View source: R/centrality-batch8.R
| centrality_community_hub_bridge | R Documentation |
Ghalmane, El Hassouni and Cherifi's (2019) score for nodes that are both hubs inside their community and bridges between communities:
CHB(i) = |C_i| \, k^{intra}_i + NNC_i \, k^{inter}_i,
where |C_i| is the number of nodes in i's own community,
k^{intra}_i and k^{inter}_i its numbers of links inside and
outside that community, and NNC_i the number of other
communities it is linked to (eqs. 2 to 4 of the paper). Higher values
mark nodes whose removal both fragments their community and cuts links
between communities. A normalized variant with the same name exists in
later work by the same group; this is the original raw form.
centrality_community_hub_bridge(x, membership = NULL, mode = "all", ...)
x |
Network input (matrix, igraph, network, cograph_network, tna object). |
membership |
Community labels, one per node. Required; without it
the function warns and returns |
mode |
For directed networks: |
... |
Additional arguments passed to |
Under mode = "out" or "in" only out- or in-links count;
the default ignores direction. Edge weights are ignored.
Named numeric vector, one value per node.
Raises an error of class cograph_bad_membership when
membership is not one non-missing label per node.
Ghalmane, Z., El Hassouni, M., & Cherifi, H. (2019). Immunization of networks with non-overlapping community structure. Social Network Analysis and Mining, 9, 45.
centrality_modularity_vitality,
centrality_participation.
adj <- matrix(0, 6, 6)
adj[cbind(c(1, 1, 2, 4, 4, 5, 3), c(2, 3, 3, 5, 6, 6, 4))] <- 1
adj <- adj + t(adj)
rownames(adj) <- colnames(adj) <- LETTERS[1:6]
centrality_community_hub_bridge(adj, membership = c(1, 1, 1, 2, 2, 2))
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