A soft modularity function for detecting fuzzy communities in social networks
Document Type
Article
Publication Date
12-1-2013
Abstract
We discuss a new formulation of a fuzzy validity index that generalizes the Newman-Girvan (NG) modularity function. The NG function serves as a cluster validity functional in community detection studies. The input data is an undirected weighted graph that represents, e.g., a social network. Clusters correspond to socially similar substructures in the network. We compare our fuzzy modularity with two existing modularity functions using the well-studied Karate Club and American College Football datasets.© 2013 IEEE.
Publication Title
IEEE Transactions on Fuzzy Systems
Recommended Citation
Havens, T.,
Bezdek, J.,
Leckie, C.,
Ramamohanarao, K.,
&
Palaniswami, M.
(2013).
A soft modularity function for detecting fuzzy communities in social networks.
IEEE Transactions on Fuzzy Systems,
21(6), 1170-1175.
http://doi.org/10.1109/TFUZZ.2013.2245135
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/11018