igraph (version 0.7.0)

infomap.community: Infomap community finding

Description

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

Usage

infomap.community (graph, e.weights = NULL, v.weights = NULL,
                   nb.trials = 10, modularity = TRUE)

Arguments

graph

The input graph.

e.weights

If not NULL, then a numeric vector of edge weights. The length must match the number of edges in the graph. By default the weight edge attribute is used as weights. If it is not present, then all edge

v.weights

If not NULL, then a numeric vector of vertex weights. The length must match the number of vertices in the graph. By default the weight vertex attribute is used as weights. If it is not present, then a

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.

Value

• infomap.community returns a communities object, please see the communities manual page for details.

concept

Community structure

Details

Please see the details of this method in the references given below.

References

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, http://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, http://arxiv.org/abs/0906.1405.

See Also

Other community finding methods and communities.

Examples

## Zachary's karate club
g <- graph.famous("Zachary")

imc <- infomap.community(g)
membership(imc)
communities(imc)