Community detection using Newman spectral methods to maximize modularity
Project description
Python implementation of Newman’s spectral methods to maximize modularity.
- See:
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
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
All the datasets in ./data comes from http://www-personal.umich.edu/~mejn/netdata/
Specifically, big_10_football_directed.gml is compiled by myself to test community detection for directed network. I combined data from http://www.sports-reference.com/cfb/conferences/big-ten/2005-schedule.html and the original football.gml to define the edge directions.
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