A statistical approach to social network monitoring

Ebrahim Mazrae Farahani, Reza Baradaran Kazemzadeh, Rassoul Noorossana and Ghazaleh Rahimian

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 22, 11272-11288

Abstract: Social network monitoring consists of monitoring changes in networks with the aim of detecting significant ones and attempting to identify assignable cause(s) contributing to the occurrence of a change. This paper proposes a method that helps to overcome some of the weaknesses of the existing methods. A Poisson regression model for the probability of the number of communications between network members as a function of vertex attributes is constructed. Multivariate exponentially weighted moving average (MEWMA) and multivariate cumulative sum (MCUSUM) control charts are used to monitor the network formation process. The results indicate more efficient performance for the MEWMA chart in identifying significant changes.

Date: 2017
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DOI: 10.1080/03610926.2016.1263741

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