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

Journal of Optimization in Industrial Engineering

مقاله 11، دوره 13، شماره 1، شهریور 2020، صفحه 131-143   

نوع مقاله: Original Manuscript

شناسه دیجیتال (DOI): 10.22094/joie.2019.581174.1615

نویسندگان

Farshid Rajabi؛ Abbas Saghaei^* ؛ Soheil Sadinejad

Industrial Engineering Department, School of Engineering, Science and Research Branch, Islamic Azad University (Hesarak Ave. Ashrafi Esfehani blvd.), Tehran, Iran.

چکیده

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.

کلیدواژه‌ها

Statistical Process Control؛ ERGM؛ Social network؛ Change detection

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