Finding Communities in a Network

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In this tutorial, you'll use Clair::Network::CFNetwork to find the communities in the Karate Club network.

Contents

Read the Network file

The Karate Club network is provided in GML format. Therefore, we will use Clair::Network::Reader::GML to read it. 

use Clair::Network::Reader::GML;
my $reader = new Clair::Network::Reader::GML();
my $net = $reader->read_network("karate.gml");

Create Clair::Network::CFNetwork instance

Next, create an instance of Clair::Network::CFNetwork and read the network into it. 

use Clair::Network::CFNetwork;
my $cfn = Clair::Network::CFNetwork();
$cfn->read_network($net);

Find the communities in the network

Now, you can run the community finding algorithm. 

$cfn->communityFind();

This will create a file named Karate.bestComm in the current directory. This file contains the optimal node labeling computed by the algorithm. Each line of the file has the format node community

Code

The code used in this tutorial is 

#!/usr/bin/perl 
use Clair::Network::Reader::GML;
use Clair::Network::CFNetwork;

my $reader = new Clair::Network::Reader::GML(name=>"Karate");
my $net = $reader->read_network("karate.gml");
my $cfn = new Clair::Network::CFNetwork();
$cfn->read_network($net);
$cfn->communityFind(dirname => "results");

Results

The content of Karate.bestComm after running running the code above should be something like 

1 1
2 1
3 7
4 7
5 1
6 7
7 7
8 7
9 1
10 1
11 22
12 1
13 1
14 1
15 1
16 1
17 1
18 22
19 1
20 22
21 1
22 22
23 7
24 1
25 1
26 22
27 7
28 7
29 7
30 1
31 1
32 22
33 22
34 22

This means that nodes 1, 2, 5, 9, 10, 12, 13, 14, 15, 16, 17, 19, 21, 24, 25, 30, and 31 are all in the same community and so on.

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