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
DOIONLINE NO - IJASEAT-IRAJ-DOIONLINE-16002
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Copyright: © Institute of Research and Journals
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Published on 2019-10-17 |
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