Network Community Discovery Method Based on User Link and Interest

In order to enhance the service quality of network community, satisfy the growing demand of community users, this paper analyzes the content of network community from different aspects and provides a comprehensive method to divide the network community user group. On one hand, this method use link analysis techniques to study hyperlink, calculate the number of output links and input links, and then construct the diagram of community user relationship and divide user group. On the other hand, this method analyzes user´s interest which is expressed in the published articles and reviews based on support vector machine (SVM) classification. We use clustering to divide group based on the characteristics of the user´s interest. A comparative analysis of the different results can get the final result with higher accuracy and reliability. At last, we use software of social network analysis to evaluate the results. This method provides a theoretical basis and technical means for network community application´s optimization and personalized services.