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Leiden Community Detection

Source: R/communities.R
community_leiden.Rd

The Leiden algorithm, a refinement of the Louvain algorithm that guarantees well-connected communities. It optimizes the Constant Potts Model (CPM) or modularity. The graph must be undirected; a directed graph raises an igraph error.

Usage

community_leiden(
  x,
  weights = NULL,
  resolution = 1,
  objective_function = c("CPM", "modularity"),
  beta = 0.01,
  initial_membership = NULL,
  n_iterations = 2,
  vertex_weights = NULL,
  seed = NULL,
  ...
)

com_ld(
  x,
  weights = NULL,
  resolution = 1,
  objective_function = c("CPM", "modularity"),
  beta = 0.01,
  initial_membership = NULL,
  n_iterations = 2,
  vertex_weights = NULL,
  seed = NULL,
  ...
)

Arguments

x

Network input.

weights

Edge weights. NULL uses the network weights and NA runs unweighted. Negative weights are replaced by their absolute values.

resolution

Resolution parameter. Default 1. With the default CPM objective and resolution 1, a network with weights below 1 is typically split into single-node communities.

objective_function

Optimization objective, "CPM" (default) or "modularity".

beta

Randomness parameter of the refinement step. Default 0.01.

initial_membership

Initial community assignments (optional).

n_iterations

Number of iterations. Default 2. A negative value iterates until the partition no longer changes.

vertex_weights

Vertex weights for the CPM objective.

seed

Random seed for reproducibility. Default NULL.

...

Passed to to_igraph, whose only other argument is directed; anything else raises an "unused argument" error.

Value

A cograph_communities data frame with columns node and community. See communities for its attributes.

References

Traag, V.A., Waltman, L., & van Eck, N.J. (2019). From Louvain to Leiden: guaranteeing well-connected communities. Scientific Reports, 9, 5233.

Examples

community_leiden(to_undirected(regulation_net), objective_function = "modularity",
                 seed = 1)
#> Community structure (leiden)
#>   Nodes: 10  | Communities: 2  | Modularity: NA 
#>   Sizes: 5, 5 
#> 
#>        node community
#>     Explore         1
#>        Plan         2
#>     Monitor         2
#>       Adapt         1
#>     Reflect         1
#>     Discuss         1
#>  Synthesize         1
#>    Evaluate         2
#>      Create         2
#>       Share         2