Detecting Communities in Weighted Graphs

Input

A weighted graph G. See graph.txt file as a sample for the input graph format. It's a CSV file where each line has the following format:

u,v,w 

Above line specifies that there is an edge between node u and v with positive weight w. The lowest id should be zero and the nodes id's increase. If you want to used this code for an unweighted graph, simply set the weight equal to one on each input line.

Output

This code runs Girvan-Newman algorithm and returns a list of detected communities with maximum modularity.

Dependencies

For running the python code, you need to install Python 3 and NetworkX package on your machine. Check link below for more details:

https://networkx.github.io/documentation/latest/install.html

Girvan-Newman Algorithm Description

You can find the details for how Girvan-Newman algorithm works from the following link:

http://www.kazemjahanbakhsh.com/codes/cmty.html

How to run Python script

python cmty.py graph.txt

If you have any question about the code or you want to report a bug, please contact me @ k DOT jahanbakhsh AT gmail DOT com.

Licence

Copyright (c) 2013 Black Square Media Ltd. All rights reserved.
(The MIT License)

Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
'Software'), to deal in the Software without restriction, including
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permit persons to whom the Software is furnished to do so, subject to
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The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.

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