| community_infomap | R Documentation |
Information-theoretic community detection based on random walk dynamics. Minimizes the map equation (description length of random walks).
community_infomap(
x,
weights = NULL,
v.weights = NULL,
nb.trials = 10,
modularity = TRUE,
seed = NULL,
...
)
com_im(
x,
weights = NULL,
v.weights = NULL,
nb.trials = 10,
modularity = TRUE,
seed = NULL,
...
)
x |
Network input |
weights |
Edge weights for transitions. NULL uses network weights. |
v.weights |
Vertex weights (teleportation weights). |
nb.trials |
Number of optimization trials. Default 10. |
modularity |
Logical; calculate modularity? Default TRUE. |
seed |
Random seed for reproducibility. Default NULL. |
... |
Additional arguments passed to |
A cograph_communities object
A cograph_communities object. See detect_communities.
Rosvall, M., & Bergstrom, C.T. (2008). Maps of random walks on complex networks reveal community structure. PNAS, 105(4), 1118-1123.
if (requireNamespace("igraph", quietly = TRUE)) {
g <- igraph::make_graph("Zachary")
comm <- community_infomap(g, nb.trials = 20)
}
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