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+gn(1) -- Find communities using the Girvan-Newman algorithm
+======
+
+## SYNOPSIS
+
+`gn` <graph_in> 
+
+## DESCRIPTION
+
+`gn` finds the communities in <graph_in> using the Girvan-Newman
+algorithm, based on the successive removal of edges with high
+betweenness. The program prints on STDOUT the partition corresponding
+to the highest value of the modularity function, and reports on STDERR
+the number of communities after each edge removal and the
+corresponding value of modularity. 
+
+`N.B.`: the program recomputes the edge betweenness of the graph after
+the removal of each edge, so it is not feasible to use it on large
+graphs.
+
+## PARAMETERS
+
+* <graph_in>:
+    undirected input graph (edge list). If is equal to `-` (dash), read
+    the edge list from STDIN.
+
+## OUTPUT
+
+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 (connected
+components) after the removal of each edge, and the corresponding
+value of modularity, 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 edge has been
+removed and `Q_i` is the corresponding value of modularity. 
+
+## EXAMPLES
+
+We can use `gn` to find communities in the graph `karate_club_unweighted.txt`
+(Zachary Karate Club network) with the command:
+
+        $ gn karate_club_unweighted.net 2> karate_gn_trace
+        ### nc: 4 Q_max: 0.365631
+        0 1
+        1 1
+        2 2
+        3 1
+        4 3
+        5 3
+        6 3
+        ...
+        30 2
+        31 2
+        32 2
+        33 2
+        $ 
+        
+In this run, the command has found a partition with 4 communities
+corrisponding to a modularity Q=0.365631. Notice that node 0, 1, 3,
+are in community 1, node 2 is in community 2, node 4,5,6, are in
+community 3 and so forth. In general, different runs will provide
+different partitions, since any tie in betweenness values is broke by
+choosing one of the edges with equal betweenness uniformly at
+random. In this example, we have chosen to save the information about
+number of communities and modularity after each edge removal in the
+file `karate_gn_trace`.
+
+## SEE ALSO
+
+modularity(1), cnm(1), label_prop(1)
+
+## REFERENCES
+
+* M\. Girvan and M. E. J. Newman. "Community structure in social and
+  biological networks". P. Natl. Acad. Sci. USA 99 (2002), 7821--7826.
+
+* V\. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles,
+  Methods and Applications", Appendix 17, Cambridge University Press
+  (2017)
+
+* V\. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles,
+  Methods and Applications", Chapter 9, Cambridge University Press
+  (2017)
+
+## AUTHORS
+
+(c) Vincenzo 'KatolaZ' Nicosia 2009-2017 `<v.nicosia@qmul.ac.uk>`.