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

Author :Y. Sunecher, N. Mamode Khan

Article Citation :Y. Sunecher ,N. Mamode Khan , (2019 ) " Using A Bivariate Longitudinal Poisson Model to Analyze Dependencies between Social Networking Services: Facebook and LinkedIn " , International Journal of Advances in Science, Engineering and Technology(IJASEAT) , pp. 45-49, Volume-7,Issue-2, Spl. Iss-1

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.

Type : Research paper

Published : Volume-7,Issue-2, Spl. Iss-1

	|		PDF	|	Viewed - 9	|	Published on 2019-10-17