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+ <title>cnm(1) - Find communities using greedy modularity optimisation</title>
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+<body id='manpage'>
+ <div class='mp' id='man'>
+
+ <div class='man-navigation' style='display:none'>
+ <a href="#NAME">NAME</a>
+ <a href="#SYNOPSIS">SYNOPSIS</a>
+ <a href="#DESCRIPTION">DESCRIPTION</a>
+ <a href="#PARAMETERS">PARAMETERS</a>
+ <a href="#OUTPUT">OUTPUT</a>
+ <a href="#EXAMPLES">EXAMPLES</a>
+ <a href="#SEE-ALSO">SEE ALSO</a>
+ <a href="#REFERENCES">REFERENCES</a>
+ <a href="#AUTHORS">AUTHORS</a>
+ </div>
+
+ <ol class='man-decor man-head man head'>
+ <li class='tl'>cnm(1)</li>
+ <li class='tc'>www.complex-networks.net</li>
+ <li class='tr'>cnm(1)</li>
+ </ol>
+
+ <h2 id="NAME">NAME</h2>
+<p class="man-name">
+ <code>cnm</code> - <span class="man-whatis">Find communities using greedy modularity optimisation</span>
+</p>
+
+<h2 id="SYNOPSIS">SYNOPSIS</h2>
+
+<p><code>cnm</code> <var>graph_in</var></p>
+
+<h2 id="DESCRIPTION">DESCRIPTION</h2>
+
+<p><code>cnm</code> finds the communities in <var>graph_in</var> 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.</p>
+
+<h2 id="PARAMETERS">PARAMETERS</h2>
+
+<dl>
+<dt><var>graph_in</var></dt><dd> undirected input graph (edge list). If is equal to <code>-</code> (dash), read
+ the edge list from STDIN.</dd>
+</dl>
+
+
+<h2 id="OUTPUT">OUTPUT</h2>
+
+<p>The program prints on STDOUT the partition corresponding to the
+highest value of modularity, in the format:</p>
+
+<pre><code> ## nc: NUM_COMM Q_max: Q_MAX
+ node_1 comm_1
+ node_2 comm_2
+ node_3 comm_3
+ ...
+</code></pre>
+
+<p>where <code>comm_i</code> is the community to which <code>node_i</code> belongs. The first
+output line reports the number of communities <code>NUM_COMM</code> and the
+corresponding value of modularity <code>Q_MAX</code> of the partition.</p>
+
+<p>The program prints on STDERR the number of communities and the
+corresponding value of modularity at each step, in the format:</p>
+
+<pre><code> nc_1 Q_1
+ nc_2 Q_2
+ nc_3 Q_3
+ ....
+</code></pre>
+
+<p>where <code>nc_i</code> is the number of communities after the i-th marge and
+<code>Q_i</code> is the corresponding value of modularity. Since the algorithm
+merges two communities at each step, the values <code>nc_1</code>, <code>nc_2</code>,
+<code>nc_3</code>, etc. will be equal to <code>N-1</code>, <code>N-2</code>, <code>N-3</code>, etc.</p>
+
+<h2 id="EXAMPLES">EXAMPLES</h2>
+
+<p>We can use <code>cnm</code> to find communities in the graph
+<code>karate_club_unweighted.net</code> (Zachary Karate Club network) with the
+command:</p>
+
+<pre><code> $ cnm karate_club_unweighted.net 2&gt; 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
+ $
+</code></pre>
+
+<p>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 <code>karate_cnm_trace</code>.</p>
+
+<h2 id="SEE-ALSO">SEE ALSO</h2>
+
+<p><a class="man-ref" href="modularity.1.html">modularity<span class="s">(1)</span></a>, <a class="man-ref" href="gn.1.html">gn<span class="s">(1)</span></a>, <a class="man-ref" href="label_prop.1.html">label_prop<span class="s">(1)</span></a></p>
+
+<h2 id="REFERENCES">REFERENCES</h2>
+
+<ul>
+<li><p>A. Clauset, M. E. J. Newman, and C. Moore. "Finding community
+structure in very large networks". Phys. Rev. E 70 (2004), 066111.</p></li>
+<li><p>V. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles,
+Methods and Applications", Appendix 18, Cambridge University Press
+(2017)</p></li>
+<li><p>V. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles,
+Methods and Applications", Chapter 9, Cambridge University Press
+(2017)</p></li>
+</ul>
+
+
+<h2 id="AUTHORS">AUTHORS</h2>
+
+<p>(c) Vincenzo 'KatolaZ' Nicosia 2009-2017 <code>&lt;v.nicosia@qmul.ac.uk&gt;</code>.</p>
+
+
+ <ol class='man-decor man-foot man foot'>
+ <li class='tl'>www.complex-networks.net</li>
+ <li class='tc'>September 2017</li>
+ <li class='tr'>cnm(1)</li>
+ </ol>
+
+ </div>
+</body>
+</html>