Genetic clustering of social networks using random walks

Authors:
Aykut Firat;Sangit Chatterjee;Mustafa Yilmaz
Affiliations:
College of Business Administration, Northeastern University, Boston, MA 02115, USA;College of Business Administration, Northeastern University, Boston, MA 02115, USA;College of Business Administration, Northeastern University, Boston, MA 02115, USA
Venue:
Computational Statistics & Data Analysis
Year:
2007

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Abstract

In the era of globalization, traditional theories and models of social systems are shifting their focus from isolation and independence to networks and connectedness. Analyzing these new complex social models is a growing, and computationally demanding area of research. In this study, we investigate the integration of genetic algorithms (GAs) with a random-walk-based distance measure to find subgroups in social networks. We test our approach by synthetically generating realistic social network data sets. Our clustering experiments using random-walk-based distances reveal exceptionally accurate results compared with the experiments using Euclidean distances.