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      Permanent link:
      https://www.ias.ac.in/article/fulltext/pram/087/06/0084

    • Keywords

       

      Complex network; degree correlation; Pearson coefficient.

    • Abstract

       

      Many real-world networks such as the protein–protein interaction networks and metabolic networks often display nontrivial correlations between degrees of vertices connected by edges. Here, we analyse the statistical methods used usually to describe the degree correlation in the networks, and analytically give linear relation in the degree correlation. It provides a simple and interesting perspective on the analysis of the degree correlation in networks, which is usefully complementary to the existing methods for degree correlation in networks. Especially, the slope in the linear relation corresponds exactly to the degree correlation coefficient in networks, meaning that it can not only characterize the level of degree correlation in networks, but also reflects the speed that the average nearest neighbours’ degree varies with the vertex degree. Finally, we applied our results to several real-world networks, validating the conclusions of the linear analysis of degree correlation. We hope that the work in this paper can be helpful for further understanding the degree correlation in complex networks.

    • Author Affiliations

       

      JU XIANG1 2 3 TAO HU4 YAN ZHANG5 KE HU6 YAN-NI TANG3 YUAN-YUAN GAO3 KE DENG7

      1. Neuroscience Research Center, Changsha Medical University, Changsha 410219, China
      2. Department of Anatomy, Histology and Embryology, Changsha Medical University, Changsha 410219, China
      3. Department of Basic Medical Sciences, Changsha Medical University, Changsha 410219, China
      4. College of Science, Qi Lu University of Technology, Jinan 250353, Shandong, China
      5. Department of Computer Science, Changsha Medical University, Changsha 410219, China
      6. Department of Physics, Xiangtan University, Xiangtan 411105, Hunan, China
      7. Department of Physics, Jishou University, Jishou 416000, Hunan, China
    • Dates

       
  • Pramana – Journal of Physics | News

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