View source: R/centrality-batch8.R
| centrality_s_shell | R Documentation |
Liu, Tang, Do and Hui's (2017) strength-based generalization of k-shell for identifying spreaders. Each link is given an asymmetric weight from the topology alone,
w_{ij} = 1 + (k_i \, k^{out}_j)^a,
where k^{out}_j is the number of j's neighbors that lie
outside i's closed neighborhood (links that lead a spreading
process to new territory), and each node's strength is
s_i = \sum_{j \in N(i)} w_{ij}. The graph is then peeled like a
k-shell but by strength: the minimum remaining strength is the
threshold, everything at or below it is removed (neighbors lose the
corresponding w_{ji}), removals cascade until the threshold holds,
and the removed nodes receive the next shell index. Higher index = more
central. With a = 0 the shells are the dense ranks of the k-core
numbers.
centrality_s_shell(x, s_shell_a = 0.5, ...)
x |
Network input (matrix, igraph, network, cograph_network, tna object). |
s_shell_a |
Exponent |
... |
Additional arguments passed to |
The index is an ordinal counter (1 = outermost shell), not a strength
value, so it is not comparable across graphs. Isolates form shell 1 on
their own, shifting every other shell up by one, as the paper's rule
implies. Direction, edge weights and self-loops are ignored. The paper's
robust default is a = 0.5.
Validated against the shell peeled at each threshold being exactly the
complement of the maximal subgraph in which every node keeps strength
above the threshold (brute force over all vertex subsets), and against
k-core dense ranks at a = 0.
Named integer vector of shell indices, one per node.
Liu, Y., Tang, M., Do, Y., & Hui, P. M. (2017). Accurate ranking of influential spreaders in networks based on dynamically asymmetric link weights. Physical Review E, 96(2), 022323.
centrality_coreness for the k-shell index.
adj <- matrix(0, 6, 6)
adj[cbind(c(1, 2, 1, 3, 4, 5), c(2, 3, 3, 4, 5, 6))] <- 1
adj <- adj + t(adj)
rownames(adj) <- colnames(adj) <- LETTERS[1:6]
centrality_s_shell(adj)
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