Performance Evaluation of Social Network Using Data Mining Techniques

  • Mrutyunjaya Panda
  • Ajith Abraham
  • Sachidananda Dehuri
  • Manas Ranjan Patra


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.


Social Network Tabu Search Social Network Analysis Social Network Site Betweenness Centrality 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag London 2012

Authors and Affiliations

  • Mrutyunjaya Panda
    • 1
  • Ajith Abraham
    • 2
  • Sachidananda Dehuri
    • 3
  • Manas Ranjan Patra
    • 4
  1. 1.Department of ECEGandhi Institute for Technological Advancement (GITA)BhubaneswarIndia
  2. 2.Machine Intelligence Research Labs (MIR labs)Scientific Network for Innovation and Research ExcellenceAuburnUSA
  3. 3.Department of Computer and Information TechnologyF.M. UniversityBalasoreIndia
  4. 4.Department of Computer ScienceBerhampur UniversityGanjamIndia

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