Use this if you are using igraph from R
cluster_infomap {igraph} | R Documentation |
Find community structure that minimizes the expected description length of a random walker trajectory
cluster_infomap(
graph,
e.weights = NULL,
v.weights = NULL,
nb.trials = 10,
modularity = TRUE
)
graph |
The input graph. |
e.weights |
If not |
v.weights |
If not |
nb.trials |
The number of attempts to partition the network (can be any integer value equal or larger than 1). |
modularity |
Logical scalar, whether to calculate the modularity score of the detected community structure. |
Please see the details of this method in the references given below.
cluster_infomap
returns a communities
object,
please see the communities
manual page for details.
Martin Rosvall wrote the original C++ code. This was ported to be more igraph-like by Emmanuel Navarro. The R interface and some cosmetics was done by Gabor Csardi csardi.gabor@gmail.com.
The original paper: M. Rosvall and C. T. Bergstrom, Maps of information flow reveal community structure in complex networks, PNAS 105, 1118 (2008) doi: 10.1073/pnas.0706851105, https://arxiv.org/abs/0707.0609
A more detailed paper: M. Rosvall, D. Axelsson, and C. T. Bergstrom, The map equation, Eur. Phys. J. Special Topics 178, 13 (2009). doi: 10.1140/epjst/e2010-01179-1, https://arxiv.org/abs/0906.1405.
Other community finding methods and communities
.
## Zachary's karate club
g <- make_graph("Zachary")
imc <- cluster_infomap(g)
membership(imc)
communities(imc)