Description Usage Arguments Details Value Author(s) References See Also Examples

Find community structure that minimizes the expected description length of a random walker trajectory

1 2 3 4 5 6 7 | ```
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) http://dx.doi.org/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).
http://dx.doi.org/10.1140/epjst/e2010-01179-1,
https://arxiv.org/abs/0906.1405.

Other community finding methods and `communities`

.

1 2 3 4 5 6 | ```
## Zachary's karate club
g <- make_graph("Zachary")
imc <- cluster_infomap(g)
membership(imc)
communities(imc)
``` |

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