The dynamic analysis of different viral contents in facebook using susceptible-infected-recovered (SIR) model / Nordayana Mohd Azhar

One of the world’s discoveries in the development of technology is Facebook. On Facebook, there are various types of content such as videos and breaking news. Viral content is a social sharing and website links that spread the content rapidly. It is the most effective way to share the information i...

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Main Author:	Mohd Azhar, Nordayana
Format:	Thesis
Language:	English
Published:	2020
Subjects:	Difference equations Functional equations Delay differential equations Integral equations
Online Access:	https://ir.uitm.edu.my/id/eprint/34856/1/34856.pdf
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id	my-uitm-ir.34856
record_format	uketd_dc
spelling	my-uitm-ir.348562020-10-05T05:51:29Z The dynamic analysis of different viral contents in facebook using susceptible-infected-recovered (SIR) model / Nordayana Mohd Azhar 2020-10-01 Mohd Azhar, Nordayana Difference equations. Functional equations. Delay differential equations. Integral equations One of the world’s discoveries in the development of technology is Facebook. On Facebook, there are various types of content such as videos and breaking news. Viral content is a social sharing and website links that spread the content rapidly. It is the most effective way to share the information in a given time. The main objective of this study is to analyze the dynamics of the number of sharing from two different forms of viral content on Facebook which are breaking news and video. The sub-objectives are to determine the spreading process of different viral contents over time and to describe the growth and the decline of daily views of the contents based on the usceptible-Infected-Recovered (SIR) model. The model of the system involves three state variables which are usceptible, infected, and recovered in the system of differential equations. In these three state variables, parameter β exists between susceptible and infected meanwhile parameter γ is present between infected and recovered. The SIR model that is being considered is without demography that excludes the rates of birth ,death, and immigration. At the end of this study, the results showed that two different viral contents reached the difference in their number of people that have an interest in these two contents. There are four graphs that have been produced to show the dynamic of the population from two different titles of each viral content; breaking news and videos. 2020-10 Thesis https://ir.uitm.edu.my/id/eprint/34856/ https://ir.uitm.edu.my/id/eprint/34856/1/34856.pdf text en public degree Universiti Teknologi Mara Perlis Faculty of Computer & Mathematical Sciences
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Difference equations Functional equations Delay differential equations Integral equations
spellingShingle	Difference equations Functional equations Delay differential equations Integral equations Mohd Azhar, Nordayana The dynamic analysis of different viral contents in facebook using susceptible-infected-recovered (SIR) model / Nordayana Mohd Azhar
description	One of the world’s discoveries in the development of technology is Facebook. On Facebook, there are various types of content such as videos and breaking news. Viral content is a social sharing and website links that spread the content rapidly. It is the most effective way to share the information in a given time. The main objective of this study is to analyze the dynamics of the number of sharing from two different forms of viral content on Facebook which are breaking news and video. The sub-objectives are to determine the spreading process of different viral contents over time and to describe the growth and the decline of daily views of the contents based on the usceptible-Infected-Recovered (SIR) model. The model of the system involves three state variables which are usceptible, infected, and recovered in the system of differential equations. In these three state variables, parameter β exists between susceptible and infected meanwhile parameter γ is present between infected and recovered. The SIR model that is being considered is without demography that excludes the rates of birth ,death, and immigration. At the end of this study, the results showed that two different viral contents reached the difference in their number of people that have an interest in these two contents. There are four graphs that have been produced to show the dynamic of the population from two different titles of each viral content; breaking news and videos.
format	Thesis
qualification_level	Bachelor degree
author	Mohd Azhar, Nordayana
author_facet	Mohd Azhar, Nordayana
author_sort	Mohd Azhar, Nordayana
title	The dynamic analysis of different viral contents in facebook using susceptible-infected-recovered (SIR) model / Nordayana Mohd Azhar
title_short	The dynamic analysis of different viral contents in facebook using susceptible-infected-recovered (SIR) model / Nordayana Mohd Azhar
title_full	The dynamic analysis of different viral contents in facebook using susceptible-infected-recovered (SIR) model / Nordayana Mohd Azhar
title_fullStr	The dynamic analysis of different viral contents in facebook using susceptible-infected-recovered (SIR) model / Nordayana Mohd Azhar
title_full_unstemmed	The dynamic analysis of different viral contents in facebook using susceptible-infected-recovered (SIR) model / Nordayana Mohd Azhar
title_sort	dynamic analysis of different viral contents in facebook using susceptible-infected-recovered (sir) model / nordayana mohd azhar
granting_institution	Universiti Teknologi Mara Perlis
granting_department	Faculty of Computer & Mathematical Sciences
publishDate	2020
url	https://ir.uitm.edu.my/id/eprint/34856/1/34856.pdf
_version_	1783734281518972928

The dynamic analysis of different viral contents in facebook using susceptible-infected-recovered (SIR) model / Nordayana Mohd Azhar

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