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Published on 23 October 2023
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Xing,S.;Liu,M.;Huang,K. (2023). Compartmental SICR model applied on study of celebrity worship behaviour. Applied and Computational Engineering,14,7-17.
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Compartmental SICR model applied on study of celebrity worship behaviour

Shuchang Xing *,1, Muchen Liu 2, Kehan Huang 3
  • 1 Tengzhou No.1 High School
  • 2 Shanghai Southwest Weiyu Middle School
  • 3 Chongqing No.1 Middle School

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/14/20230752

Abstract

We notice that there are lots of researches that studies celebrity worship behaviour and celebrity endorsement. Nevertheless, few go deep into a mathematical perspective, much less try to quantify this ambiguous process due to the lack of suitable models. In this research, we pioneer a new way, using SICR epidemic model, to fully describe the process of celebrity worship in details, through which we make predictions based on the basic reproduction number whether a celebrity could expand his or her fan base continuously. Meanwhile, not only do we further diversify the function of SICR model, but we also make improvements on the model itself. At the end of research, we also provide useful suggestions for celebrities and their brokerage companies about how to keep the number of their fans increasing rather than hit a bottleneck so quickly. The fact is that celebrities should emphasize the avoidance of negative events instead of positive publicity and be attractive to more groups of people rather than stick to one specific group only.

Keywords

celebrity worship, SICR model, sensitivity analysis, fan base, fanatic

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Cite this article

Xing,S.;Liu,M.;Huang,K. (2023). Compartmental SICR model applied on study of celebrity worship behaviour. Applied and Computational Engineering,14,7-17.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 5th International Conference on Computing and Data Science

Conference website: https://2023.confcds.org/
ISBN:978-1-83558-019-6(Print) / 978-1-83558-020-2(Online)
Conference date: 14 July 2023
Editor:Alan Wang, Marwan Omar, Roman Bauer
Series: Applied and Computational Engineering
Volume number: Vol.14
ISSN:2755-2721(Print) / 2755-273X(Online)

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