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...

Full description

Saved in:
Bibliographic Details
Main Author: Mohd Azhar, Nordayana
Format: Thesis
Language:English
Published: 2020
Subjects:
Online Access:http://ir.uitm.edu.my/id/eprint/34856/1/34856.pdf
http://ir.uitm.edu.my/id/eprint/34856/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uitm.ir.34856
record_format eprints
spelling my.uitm.ir.348562020-10-05T05:51:29Z http://ir.uitm.edu.my/id/eprint/34856/ The dynamic analysis of different viral contents in facebook using susceptible-infected-recovered (SIR) model / Nordayana Mohd Azhar 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. 2020-10-01 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/34856/1/34856.pdf Mohd Azhar, Nordayana (2020) The dynamic analysis of different viral contents in facebook using susceptible-infected-recovered (SIR) model / Nordayana Mohd Azhar. Degree thesis, Universiti Teknologi Mara Perlis.
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
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
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
publishDate 2020
url http://ir.uitm.edu.my/id/eprint/34856/1/34856.pdf
http://ir.uitm.edu.my/id/eprint/34856/
_version_ 1685651244396314624
score 13.209306