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

Subject Areas : Business Management

Farshid  Rajabi ¹ (Industrial Engineering Department, School of Engineering, Science and Research Branch, Islamic Azad University (Hesarak Ave. Ashrafi Esfehani blvd.), Tehran, Iran.)
Abbas  Saghaei ² (Industrial Engineering Department, School of Engineering, Science and Research Branch, Islamic Azad University (Hesarak Ave. Ashrafi Esfehani blvd.), Tehran, Iran.)
Soheil  Sadinejad ³ (Industrial Engineering Department, School of Engineering, Science and Research Branch, Islamic Azad University (Hesarak Ave. Ashrafi Esfehani blvd.), Tehran, Iran.)

Received: 2018-12-15 Accepted : 2019-09-17 Published : 2020-06-01

Keywords: Statistical Process Control, Change detection, social network, ERGM,

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.

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