• Title of article

    Power-law link strength distribution in paper cocitation networks

  • Author/Authors

    Star X. Zhao1، نويسنده , , Fred Y. Ye2، نويسنده , , *، نويسنده ,

  • Issue Information
    ماهنامه با شماره پیاپی سال 2013
  • Pages
    10
  • From page
    1480
  • To page
    1489
  • Abstract
    A network is constructed by nodes and links, thus the node degree and the link strength appear as underlying quantities in network analysis. While the power-law distribution of node degrees is verified as a basic feature of numerous real networks, we investigate whether the link strengths follow the power-law distribution in weighted networks. After testing 12 different paper cocitation networks with 2 methods, fitting in double-log scales and the Kolmogorov-Smirnov test (K-S test), we observe that, in most cases, the link strengths also follow the approximate power-law distribution. The results suggest that the power-law type distribution could emerge not only in nodes and informational entities, but also in links and informational connections.
  • Keywords
    information flow , sociocultural aspects , international aspects , technology impact , Information policy
  • Journal title
    Journal of the American Society for Information Science and Technology
  • Serial Year
    2013
  • Journal title
    Journal of the American Society for Information Science and Technology
  • Record number

    994901