A Soft Modularity Function For Detecting Fuzzy Communities in Social Networks

Author

Havens, Timothy C. ; Bezdek, James C. ; Leckie, Christopher ; Ramamohanarao, Kotagiri ; Palaniswami, Marimuthu

Author_Institution

Depts. of Electr. & Comput. Eng. & Comput. Sci., Michigan Technol. Univ., Houghton, MI, USA

Volume

21

Issue

6

fYear

2013

fDate

Dec. 2013

Firstpage

1170

Lastpage

1175

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.

Keywords

fuzzy set theory; graph theory; social networking (online); American College Football datasets; Karate Club; NG modularity function; Newman-Girvan modularity function; cluster validity functional; fuzzy community detection; fuzzy modularity; fuzzy validity index; social networks; socially similar substructures; soft modularity function; undirected weighted graph; Clustering algorithms; Communities; Educational institutions; Games; Indexes; Probabilistic logic; Social network services; Clique discovery; community detection; fuzzy communities; fuzzy modularity; modularity;

fLanguage

English

Journal_Title

Fuzzy Systems, IEEE Transactions on

Publisher

ieee

ISSN

1063-6706

Type

jour

DOI

10.1109/TFUZZ.2013.2245135

Filename

6450075