Performance Evaluation of Social Network Using Data Mining Techniques

Social network research relies on a variety of data sources, depending on the problem scenario and the questions, which the research is trying to answer or inform. Social networks are very popular nowadays and the understanding of their inner structure seems to be promising area. Cluster analysis has also been an increasingly interesting topic in the area of computational intelligence and found suitable in social network analysis in its social network structure. In this chapter, we use k-cluster analysis with various performance measures to analyse some of the data sources obtained for social network analysis. Our proposed approach is intended to address the users of social network, that will not only help an organization to understand their external and internal associations but also highly necessary for the enhancement of collaboration, innovation and dissemination of knowledge. M. Panda ( ) Department of ECE, Gandhi Institute for Technological Advancement (GITA), Bhubaneswar, Odisha, India e-mail: [email protected] A. Abraham Machine Intelligence Research Labs (MIR labs), Scientific Network for Innovation and Research Excellence, Auburn, WA, USA e-mail: [email protected] S. Dehuri Department of Computer and Information Technology, F.M. University, Balasore, India e-mail: [email protected] M.R. Patra Department of Computer Science, Berhampur University, Ganjam, India e-mail: [email protected] A. Abraham (ed.), Computational Social Networks: Mining and Visualization, DOI 10.1007/978-1-4471-4054-2 2, © Springer-Verlag London 201 25 2