Analysing the dynamics of online advertising via instagram feed using susceptible-infected-recovered model / Nurul Natasya Che Abdul Halim

The Instagram Feed becomes a marketing platform that has been used extensively by many marketers to advertise their products. However, most of the marketers who have used the Instagram Feed cannot predict whether the products that they have posted will be viral or not. If the product goes viral, the...

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Main Author: Abdul Halim, Nurul Natasya Che
Format: Thesis
Language:English
Published: 2021
Subjects:
Online Access:http://ir.uitm.edu.my/id/eprint/45004/1/45004.pdf
http://ir.uitm.edu.my/id/eprint/45004/
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spelling my.uitm.ir.450042021-04-22T07:41:49Z http://ir.uitm.edu.my/id/eprint/45004/ Analysing the dynamics of online advertising via instagram feed using susceptible-infected-recovered model / Nurul Natasya Che Abdul Halim Abdul Halim, Nurul Natasya Che Telemarketing. Internet marketing Difference equations. Functional equations. Delay differential equations. Integral equations The Instagram Feed becomes a marketing platform that has been used extensively by many marketers to advertise their products. However, most of the marketers who have used the Instagram Feed cannot predict whether the products that they have posted will be viral or not. If the product goes viral, they do not have any knowledge about the time the product starts to viral and the duration of the virality. Furthermore, there are uncertainties of the number of followers, likes and comments which affect the virality of products. The main objective of this study is to analyse the dynamics of online advertising through Instagram Feed using the epidemiological model. The model consists of three state variables namely susceptible (S) which represents the Instagram users who receive the advertising information, infected (I) represents the number of Instagram followers and recovered (R) represents the number of Instagram users who follow advertising page but stop viewing or sharing the information. Hence, it is known as SIR model. Three Instagram accounts had been chosen, there were @theduckgroup, @wawacosmeticshq and @cakenis. All the information about the number of followers, likes, views and shares had been collected for each Instagram account. The result showed that the advertisement could be more viral if the value of parameter β which is the transmission rate between the Instagram users and Instagram followers is higher. Meanwhile, the result revealed that there were not many changes with the virality as parameter γ, the rate of people who received and viewed advertisement post then stop viewing and like the posts increases. The advertisement would be viral faster when the initial number of Instagram followers who received and shared the advertisement increased. This study found that the advertisement post of @theduckgroup is the most viral. 2021-04-08 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/45004/1/45004.pdf Abdul Halim, Nurul Natasya Che (2021) Analysing the dynamics of online advertising via instagram feed using susceptible-infected-recovered model / Nurul Natasya Che Abdul Halim. 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 Telemarketing. Internet marketing
Difference equations. Functional equations. Delay differential equations. Integral equations
spellingShingle Telemarketing. Internet marketing
Difference equations. Functional equations. Delay differential equations. Integral equations
Abdul Halim, Nurul Natasya Che
Analysing the dynamics of online advertising via instagram feed using susceptible-infected-recovered model / Nurul Natasya Che Abdul Halim
description The Instagram Feed becomes a marketing platform that has been used extensively by many marketers to advertise their products. However, most of the marketers who have used the Instagram Feed cannot predict whether the products that they have posted will be viral or not. If the product goes viral, they do not have any knowledge about the time the product starts to viral and the duration of the virality. Furthermore, there are uncertainties of the number of followers, likes and comments which affect the virality of products. The main objective of this study is to analyse the dynamics of online advertising through Instagram Feed using the epidemiological model. The model consists of three state variables namely susceptible (S) which represents the Instagram users who receive the advertising information, infected (I) represents the number of Instagram followers and recovered (R) represents the number of Instagram users who follow advertising page but stop viewing or sharing the information. Hence, it is known as SIR model. Three Instagram accounts had been chosen, there were @theduckgroup, @wawacosmeticshq and @cakenis. All the information about the number of followers, likes, views and shares had been collected for each Instagram account. The result showed that the advertisement could be more viral if the value of parameter β which is the transmission rate between the Instagram users and Instagram followers is higher. Meanwhile, the result revealed that there were not many changes with the virality as parameter γ, the rate of people who received and viewed advertisement post then stop viewing and like the posts increases. The advertisement would be viral faster when the initial number of Instagram followers who received and shared the advertisement increased. This study found that the advertisement post of @theduckgroup is the most viral.
format Thesis
author Abdul Halim, Nurul Natasya Che
author_facet Abdul Halim, Nurul Natasya Che
author_sort Abdul Halim, Nurul Natasya Che
title Analysing the dynamics of online advertising via instagram feed using susceptible-infected-recovered model / Nurul Natasya Che Abdul Halim
title_short Analysing the dynamics of online advertising via instagram feed using susceptible-infected-recovered model / Nurul Natasya Che Abdul Halim
title_full Analysing the dynamics of online advertising via instagram feed using susceptible-infected-recovered model / Nurul Natasya Che Abdul Halim
title_fullStr Analysing the dynamics of online advertising via instagram feed using susceptible-infected-recovered model / Nurul Natasya Che Abdul Halim
title_full_unstemmed Analysing the dynamics of online advertising via instagram feed using susceptible-infected-recovered model / Nurul Natasya Che Abdul Halim
title_sort analysing the dynamics of online advertising via instagram feed using susceptible-infected-recovered model / nurul natasya che abdul halim
publishDate 2021
url http://ir.uitm.edu.my/id/eprint/45004/1/45004.pdf
http://ir.uitm.edu.my/id/eprint/45004/
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score 13.18916