• DocumentCode
    43456
  • Title

    Edge Balance Ratio: Power Law From Vertices to Edges in Directed Complex Network

  • Author

    Xiaohan Wang ; Zhaoqun Chen ; Pengfei Liu ; Yuantao Gu

  • Author_Institution
    Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
  • Volume
    7
  • Issue
    2
  • fYear
    2013
  • fDate
    Apr-13
  • Firstpage
    184
  • Lastpage
    194
  • Abstract
    Power law distribution is common in real-world networks including online social networks. Many studies on complex networks focus on the characteristics of vertices, which are always proved to follow the power law. However, few researches have been done on edges in directed networks. In this paper, edge balance ratio is firstly proposed to measure the balance property of edges in directed networks. Based on edge balance ratio, balance profile and positivity are put forward to describe the balance level of the whole network. Then the distribution of edge balance ratio is theoretically analyzed. In a directed network whose vertex in-degree follows the power law with scaling exponent γ, it is proved that the edge balance ratio follows a piecewise power law, with the scaling exponent of each section linearly dependent on γ. The theoretical analysis is verified by numerical simulations. Moreover, the theoretical analysis is confirmed by statistics of real-world online social networks, including Twitter network with 35 million users and Sina Weibo network with 110 million users.
  • Keywords
    network theory (graphs); social networking (online); Sina Weibo network; Twitter network; balance profile; directed complex network; edge balance ratio; numerical simulations; online social networks; positivity; power law distribution; scaling exponent; Communities; Complex networks; Image edge detection; Materials; Numerical simulation; Twitter; Balance profile; complex network; directed graph; edge balance ratio; microblogging network; online social network; positivity; power law;
  • fLanguage
    English
  • Journal_Title
    Selected Topics in Signal Processing, IEEE Journal of
  • Publisher
    ieee
  • ISSN
    1932-4553
  • Type

    jour

  • DOI
    10.1109/JSTSP.2013.2245299
  • Filename
    6450034