cnm - Find communities using greedy modularity optimisation
cnm graph_in
cnm finds the communities in graph_in using the greedy modularity
optimisation algorithm proposed by Clauset, Newman and Moore. The
program prints on STDOUT the partition corresponding to the highest
value of the modularity function, and reports on STDERR the number of
communities and the corresponding value of modularity at each
step. The algorithm is quite eficient and thus suitable to find
communities in large graphs.
- (dash), read
the edge list from STDIN.The program prints on STDOUT the partition corresponding to the highest value of modularity, in the format:
## nc: NUM_COMM Q_max: Q_MAX
node_1 comm_1
node_2 comm_2
node_3 comm_3
...
where comm_i is the community to which node_i belongs. The first
output line reports the number of communities NUM_COMM and the
corresponding value of modularity Q_MAX of the partition.
The program prints on STDERR the number of communities and the corresponding value of modularity at each step, in the format:
nc_1 Q_1
nc_2 Q_2
nc_3 Q_3
....
where nc_i is the number of communities after the i-th marge and
Q_i is the corresponding value of modularity. Since the algorithm
merges two communities at each step, the values nc_1, nc_2,
nc_3, etc. will be equal to N-1, N-2, N-3, etc.
We can use cnm to find communities in the graph
karate_club_unweighted.net (Zachary Karate Club network) with the
command:
$ cnm karate_club_unweighted.net 2> karate_cnm_trace
### nc: 3 Q_max: 0.380671
0 16
1 2
2 2
3 2
4 16
5 16
6 16
...
30 26
31 26
32 26
33 26
$
The program has found a partition with 3 communities corrisponding to
a modularity Q=0.380671. Notice that node 0, 4, 5, 6 are in community
16, node 1, 2, 3 are in community 2, and so forth. In this example,
we have chosen to save the information about number of communities and
modularity at each step in the file karate_cnm_trace.
modularity(1), gn(1), label_prop(1)
A. Clauset, M. E. J. Newman, and C. Moore. "Finding community structure in very large networks". Phys. Rev. E 70 (2004), 066111.
V. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles, Methods and Applications", Appendix 18, Cambridge University Press (2017)
V. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles, Methods and Applications", Chapter 9, Cambridge University Press (2017)
(c) Vincenzo 'KatolaZ' Nicosia 2009-2017 <v.nicosia@qmul.ac.uk>.