Use this if you are using igraph from R
The harmonic centrality of a vertex is the mean inverse distance to all other vertices. The inverse distance to an unreachable vertex is considered to be zero.
harmonic_centrality( graph, vids = V(graph), mode = c("out", "in", "all", "total"), weights = NULL, normalized = FALSE, cutoff = -1 )
graph |
The graph to analyze. |
vids |
The vertices for which harmonic centrality will be calculated. |
mode |
Character string, defining the types of the paths used for measuring the distance in directed graphs. “out” follows paths along the edge directions only, “in” traverses the edges in reverse, while “all” ignores edge directions. This argument is ignored for undirected graphs. |
weights |
Optional positive weight vector for calculating weighted
harmonic centrality. If the graph has a |
normalized |
Logical scalar, whether to calculate the normalized harmonic centrality. If true, the result is the mean inverse path length to other vertices, i.e. it is normalized by the number of vertices minus one. If false, the result is the sum of inverse path lengths to other vertices. |
cutoff |
The maximum path length to consider when calculating the betweenness. There is no such limit when the cutoff is negative. Note that zero cutoff means that only paths of at most length 0 are considered. |
The cutoff
argument can be used to restrict the calculation to paths
of length cutoff
or smaller only; this can be used for larger graphs
to speed up the calculation. If cutoff
is negative (which is the
default), then the function calculates the exact harmonic centrality scores.
Numeric vector with the harmonic centrality scores of all the vertices in
v
.
M. Marchiori and V. Latora, Harmony in the small-world, Physica A 285, pp. 539-546 (2000).
g <- make_ring(10) g2 <- make_star(10) harmonic_centrality(g) harmonic_centrality(g2, mode="in") harmonic_centrality(g2, mode="out") harmonic_centrality(g %du% make_full_graph(5), mode="all")