Susceptible-Infected-Recovered (SIR) Model to Measure the Virality of Breaking News on Facebook

Susceptible-Infected-Recovered (SIR) Model to Measure the Virality of Breaking News on Facebook

Authors

  • Noorzila Sharif Universiti Teknologi MARA, Perlis Branch, Arau Campus
  • Jasmani Bidin Universiti Teknologi MARA, Perlis Branch, Arau Campus
  • Ku Azlina Ku Akil Universiti Teknologi MARA, Perlis Branch, Arau Campus
  • Nur Natasha Arisha Rizan Universiti Teknologi MARA, Perlis Branch, Arau Campus

DOI:

https://doi.org/10.24191/jcrinn.v6i2.200

Keywords:

social media, Facebook, Susceptible-Infected-Recovered , virality

Abstract

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.

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Published

2021-04-01

How to Cite

Sharif, N. ., Bidin, J., Ku Akil, K. A. ., & Rizan, N. N. A. . (2021). Susceptible-Infected-Recovered (SIR) Model to Measure the Virality of Breaking News on Facebook . Journal of Computing Research and Innovation, 6(2), 55–65. https://doi.org/10.24191/jcrinn.v6i2.200

Issue

Section

General Computing

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