Use this if you are using igraph from R
cluster_leiden {igraph}  R Documentation 
Finding community structure of a graph using the Leiden algorithm of Traag, van Eck & Waltman.
cluster_leiden(
graph,
objective_function = c("CPM", "modularity"),
weights = NULL,
resolution_parameter = 1,
beta = 0.01,
initial_membership = NULL,
n_iterations = 2,
vertex_weights = NULL
)
graph 
The input graph, only undirected graphs are supported. 
objective_function 
Whether to use the Constant Potts Model (CPM) or
modularity. Must be either 
weights 
The weights of the edges. It must be a positive numeric vector,

resolution_parameter 
The resolution parameter to use. Higher resolutions lead to more smaller communities, while lower resolutions lead to fewer larger communities. 
beta 
Parameter affecting the randomness in the Leiden algorithm. This affects only the refinement step of the algorithm. 
initial_membership 
If provided, the Leiden algorithm will try to improve this provided membership. If no argument is provided, the aglorithm simply starts from the singleton partition. 
n_iterations 
the number of iterations to iterate the Leiden algorithm. Each iteration may improve the partition further. 
vertex_weights 
the vertex weights used in the Leiden algorithm. If this is not provided, it will be automatically determined on the basis of whether you want to use CPM or modularity. If you do provide this, please make sure that you understand what you are doing. 
cluster_leiden
returns a communities
object, please see the communities
manual page for details.
Vincent Traag
Traag, V. A., Waltman, L., & van Eck, N. J. (2019). From Louvain to Leiden: guaranteeing wellconnected communities. Scientific reports, 9(1), 5233. doi: 10.1038/s4159801941695z
See communities
for extracting the membership,
modularity scores, etc. from the results.
Other community detection algorithms: cluster_walktrap
,
cluster_spinglass
,
cluster_leading_eigen
,
cluster_edge_betweenness
,
cluster_fast_greedy
,
cluster_label_prop
cluster_louvain
g < graph.famous("Zachary")
# By default CPM is used
g < cluster_leiden(g, resolution_parameter=0.06)