Community Detection By Maximizing Modularity Python Implementaion of Newman Spectral Method

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Last updated on 02-23-2018

Citation and Acknowledgement

Please cite the following papers when you use these algorithms in your research:

[1] Newman, M. E. J. (2006). Modularity and community structure in networks. Proceedings of the National Academy of Sciences of the United States of America, 103(23), 8577–82. https://doi.org/10.1073/pnas.0601602103

[2] Leicht, E. A., & Newman, M. E. J. (2008). Community Structure in Directed Networks. Physical Review Letters, 100(11), 118703. https://doi.org/10.1103/PhysRevLett.100.118703

If you use my code in your paper, it would be courteous of you to thank me in your acknowledgements for providing you with implementations of the methods.

Download

PyScopus requires:

• Python 2 & Python 3 (Tested on Python 2.7 and Python 3.6)

• Numpy

• Networkx

• Scipy

1. Using pip or easy_install

The easiest way of installing is to use pip:

$ pip install python-modularity-maximization==0.0.1rc4

or easy_install

$ easy_install python-modularity-maximization==0.0.1rc4

2. Manual installation

You can also clone and install the project from its GitHub homepage like this:

$ git clone https://github.com/zhiyzuo/python-modularity-maximization.git
$ cd python-modularity-maximization/
$ python setup.py install

And then please refer to the quick start for usage.