Susceptible-Infected-Recovered (SIR) model to measure the virality of breaking news on Facebook / Noorzila Sharif ... [et al.]

Susceptible-Infected-Recovered (SIR) model has been used worldwide to measure the spreading of covid-19 in the community. Apparently, the spreading nature of the covid-19 virus and any other contagious disease is quite similar with the spreading of breaking news through social media. This study was...

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Main Authors: Sharif, Noorzila, Bidin, Jasmani, Ku Akil, Ku Azlina, Rizan, Nur Natasha Arisha
Format: Article
Language:English
Published: UiTM Cawangan Perlis 2021
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/60158/1/60158.pdf
https://ir.uitm.edu.my/id/eprint/60158/
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Institution: Universiti Teknologi Mara
Language: English
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spelling my.uitm.ir.601582022-06-22T01:13:27Z https://ir.uitm.edu.my/id/eprint/60158/ Susceptible-Infected-Recovered (SIR) model to measure the virality of breaking news on Facebook / Noorzila Sharif ... [et al.] Sharif, Noorzila Bidin, Jasmani Ku Akil, Ku Azlina Rizan, Nur Natasha Arisha Online social networks Prediction analysis Susceptible-Infected-Recovered (SIR) model has been used worldwide to measure the spreading of covid-19 in the community. Apparently, the spreading nature of the covid-19 virus and any other contagious disease is quite similar with the spreading of breaking news through social media. This study was carried out to analyze the dynamics spread of one selected news content on Facebook using SIR models with demography and without demography. From the news, the numbers of likes, comments, shares, views as well as the number of followers of the Facebook account have been collected to calculate reproduction number. For SIR without demography, the reproduction number (Ro) is 1.69, indicates that for every 100 Facebook users who received the news, they will probably share the news to other 169 Facebook users. The value of R0 is slightly lower (1.58) for SIR with demography. This preliminary study could be extended by considering a lot more observations and by testing different parameters value due to any further action imposed after the news spreading out. UiTM Cawangan Perlis 2021 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/60158/1/60158.pdf Susceptible-Infected-Recovered (SIR) model to measure the virality of breaking news on Facebook / Noorzila Sharif ... [et al.]. (2021) Journal of Computing Research and Innovation (JCRINN), 6 (2): 6. pp. 53-63. ISSN 2600-8793 https://crinn.conferencehunter.com/
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 Online social networks
Prediction analysis
spellingShingle Online social networks
Prediction analysis
Sharif, Noorzila
Bidin, Jasmani
Ku Akil, Ku Azlina
Rizan, Nur Natasha Arisha
Susceptible-Infected-Recovered (SIR) model to measure the virality of breaking news on Facebook / Noorzila Sharif ... [et al.]
description Susceptible-Infected-Recovered (SIR) model has been used worldwide to measure the spreading of covid-19 in the community. Apparently, the spreading nature of the covid-19 virus and any other contagious disease is quite similar with the spreading of breaking news through social media. This study was carried out to analyze the dynamics spread of one selected news content on Facebook using SIR models with demography and without demography. From the news, the numbers of likes, comments, shares, views as well as the number of followers of the Facebook account have been collected to calculate reproduction number. For SIR without demography, the reproduction number (Ro) is 1.69, indicates that for every 100 Facebook users who received the news, they will probably share the news to other 169 Facebook users. The value of R0 is slightly lower (1.58) for SIR with demography. This preliminary study could be extended by considering a lot more observations and by testing different parameters value due to any further action imposed after the news spreading out.
format Article
author Sharif, Noorzila
Bidin, Jasmani
Ku Akil, Ku Azlina
Rizan, Nur Natasha Arisha
author_facet Sharif, Noorzila
Bidin, Jasmani
Ku Akil, Ku Azlina
Rizan, Nur Natasha Arisha
author_sort Sharif, Noorzila
title Susceptible-Infected-Recovered (SIR) model to measure the virality of breaking news on Facebook / Noorzila Sharif ... [et al.]
title_short Susceptible-Infected-Recovered (SIR) model to measure the virality of breaking news on Facebook / Noorzila Sharif ... [et al.]
title_full Susceptible-Infected-Recovered (SIR) model to measure the virality of breaking news on Facebook / Noorzila Sharif ... [et al.]
title_fullStr Susceptible-Infected-Recovered (SIR) model to measure the virality of breaking news on Facebook / Noorzila Sharif ... [et al.]
title_full_unstemmed Susceptible-Infected-Recovered (SIR) model to measure the virality of breaking news on Facebook / Noorzila Sharif ... [et al.]
title_sort susceptible-infected-recovered (sir) model to measure the virality of breaking news on facebook / noorzila sharif ... [et al.]
publisher UiTM Cawangan Perlis
publishDate 2021
url https://ir.uitm.edu.my/id/eprint/60158/1/60158.pdf
https://ir.uitm.edu.my/id/eprint/60158/
https://crinn.conferencehunter.com/
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