DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Science, Engineering and Technology(IJASEAT)-IJASEAT |
 Journal Home Volume Issue |
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Issue |
Volume-7,Issue-2, Spl. Iss-1 ( May, 2019 ) | |||||||||
Paper Title |
Using A Bivariate Longitudinal Poisson Model to Analyze Dependencies between Social Networking Services: Facebook and LinkedIn | |||||||||
Author Name |
Y. Sunecher, N. Mamode Khan | |||||||||
Affilition |
University of Technology, Mauritius | |||||||||
Pages |
45-49 | |||||||||
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. | |||||||||
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