This function computes the Harmonic Centrality for nodes in a network. The harmonic centrality metric is defined as the denormalized reciprocal of the harmonic mean of all distances.
harmonic_centrality(
x,
vids = V(x),
mode = c("all", "out", "in"),
weights = NULL
)A numeric vector of centrality values for each node. The length of the vector is equal to the number of nodes in the network.
An igraph or a network object.
Nodes to be considered in the calculation.
A character value, indicating the type of degree to consider ("out" for out-degree, "in" for in-degree, "total" for the sum of the two). For undirected graphs, this argument is ignored. The default value is "total".
Numeric vector indicating weights of the edges.
Minoo Ashtiani, Mehdi Mirzaie, Mohieddin Jafari
BOLDI, P. & VIGNA, S. 2014. Axioms for centrality. Internet Mathematics, 00-00.
MARCHIORI, M. & LATORA, V. 2000. Harmony in the small-world. Physica A: Statistical Mechanics and its Applications, 285, 539-546.
OPSAHL, T., AGNEESSENS, F. & SKVORETZ, J. 2010. Node centrality in weighted networks: Generalizing degree and shortest paths. Social Networks, 32, 245-251.
OPSAHL, T. 2010. Closeness centrality in networks with disconnected components (http://toreopsahl.com/2010/03/20/closeness-centrality-in-networks-with-disconnected-components/)
data(zachary)
harmonic_centrality(zachary)
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