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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| Format: | Thesis |
| Language: | English |
| Published: |
2020
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| Online Access: | https://ir.uitm.edu.my/id/eprint/34856/ |
| _version_ | 1848808648792342528 |
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| author | Mohd Azhar, Nordayana |
| author_facet | Mohd Azhar, Nordayana |
| author_sort | Mohd Azhar, Nordayana |
| building | UiTM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-14T23:02:04Z |
| format | Thesis |
| id | uitm-34856 |
| institution | Universiti Teknologi MARA |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T23:02:04Z |
| publishDate | 2020 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uitm-348562020-10-05T05:51:29Z https://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 https://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. (2020) Degree thesis, thesis, Universiti Teknologi Mara Perlis. |
| 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 |
| title | 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_short | 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 |
| topic | Difference equations. Functional equations. Delay differential equations. Integral equations |
| url | https://ir.uitm.edu.my/id/eprint/34856/ |