Paper Title
Using A Bivariate Longitudinal Poisson Model to Analyze Dependencies between Social Networking Services: Facebook and LinkedIn

Abstract
Unarguably, Social Networking services such as Facebook and professional based LinkedIn are the most popular tools of communication in today’s times. Though it appears that there is a close relation between these two services but yet there is no statistical study confirming this statement. In this context, this paper proposes a sophisticated statistical model in the form of a bivariate longitudinal Poisson distribution that analyzes the number of times a sample of 360 professional connects to his or her facebook and LinkedIn accounts per day over a one week period subject to time-independent covariates such as Gender, Marital Status, Number of Children and their age. Keywords- Longitudinal, BINAR(1), Poisson, GMM.