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Applying Social Networks Analysis Methods to Discover Key Users in an Interest-Oriented Virtual Community

  • Bo-Jen Chen
  • I-Hsien Ting
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 172)

Abstract

In recent years, with the growth of Internet technology and virtual community, the users in virtual community not only play as the information receiver but also very important role to provide information. However, information overload has becoming a very serious problem and how to find information efficiently is also an important issue. In this research, we believe that users in a virtual community may affect each other, especially those with high influence. Therefore, we propose an architecture to discover the key users in a virtual community. By applying the architecture, it would be a very efficient and low cost approach. In the architecture, social networks analysis and visualization technique will be the main methods to discover the key users. In this paper, we also present an experiment to demonstrate the proposed method and the analysis results.

Keywords

Social Network Analysis Cluster Coefficient Online Social Networking Small World Small World Network 
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 Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Information ManagementNational University of KaohsiungKaohsiungTaiwan

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