• Title of article

    Monitoring of Social Network and Change Detection by Applying Statistical Process: ERGM

  • Author/Authors

    Rajabi, Frshid School of Engineering - Science and Research Branch - Islamic Azad University , Saghaei, Abbas School of Engineering - Science and Research Branch - Islamic Azad University , Sadinejad, Soheil School of Engineering - Science and Research Branch - Islamic Azad University

  • Pages
    13
  • From page
    131
  • To page
    143
  • Abstract
    The statistical modeling of social network data needs much effort because of the complex dependence structure of the tie variables. In order to formulate such dependences, the statistical exponential families of distributions can provide a flexible structure. In this regard, the statistical characteristics of the network is provided to be encapsulated within an Exponential Random Graph Model (ERGM). Applying the ERGM, in this paper, we follow to design a statistical process control through network behavior. The results demonstrated the superiority of the designed chart over the existing change detection methods in controlling the states. Additionally, the detection process is formulated for the social networks and the results are statistically analyzed.
  • Keywords
    Statistical Process Control , ERGM , Social network , Change detection
  • Journal title
    Astroparticle Physics
  • Serial Year
    2020
  • Record number

    2490833