Infomap community finding
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)
- The input graph.
- If not
NULL, then a numeric vector of edge weights. The length must match the number of edges in the graph. By default the
edge attribute is used as weights. If it is not present, then all edges are consi
- If not
NULL, then a numeric vector of vertex weights. The length must match the number of vertices in the graph. By default the
vertex attribute is used as weights. If it is not present, then all vertices
- The number of attempts to partition the network (can be any integer value equal or larger than 1).
- 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.
The original paper: M. Rosvall and C. T. Bergstrom, Maps of
information flow reveal community structure in complex networks, PNAS
105, 1118 (2008)
A more detailed paper: M. Rosvall, D. Axelsson, and C. T. Bergstrom, The map
equation, Eur. Phys. J. Special Topics 178, 13 (2009).
Other community finding methods and
## Zachary's karate club g <- make_graph("Zachary") imc <- cluster_infomap(g) membership(imc) communities(imc)