The effect of theme on the number of celebrity active fans under China Weibo data

Gaogao Dong (), Wenqi Shi (), Zhipeng Sun (), Fan Wang and Jianguo Liu
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Gaogao Dong: School of Mathematical Sciences, Jiangsu University, 212013 Zhenjiang, Jiangsu, P. R. China
Wenqi Shi: School of Mathematical Sciences, Jiangsu University, 212013 Zhenjiang, Jiangsu, P. R. China
Zhipeng Sun: School of Mathematical Sciences, Jiangsu University, 212013 Zhenjiang, Jiangsu, P. R. China
Fan Wang: School of Mathematical Sciences, Jiangsu University, 212013 Zhenjiang, Jiangsu, P. R. China†Department of Physics, Bar-Ilan University, Ramat Gan 52900, Israel
Jianguo Liu: ��Institute of Accounting and Finance, Shanghai University of Finance and Economics, No. 777, Guoding Road, Shanghai 200443, P. R. China§School of Public Management, Xinjiang University of Finance and Economics, No. 449, Beijing Middle Road, Urumqi 830012, P. R. China

International Journal of Modern Physics C (IJMPC), 2025, vol. 36, issue 10, 1-20

Abstract: Online social media platforms have emerged as integral channels for facilitating social interactions, with celebrities utilizing these platforms to engage with their fan base and cultivate a substantial following. The group of engaged fans, commonly referred to as “active fans†, represents individuals who actively communicate with celebrities and actively participate in discussions pertaining to the celebrities’ endeavors. For celebrities, the task of retaining and augmenting the count of active fans holds immense significance, as it significantly amplifies their social impact and commercial value. Here, we construct dynamic weighted active fan networks by leveraging data from 2021 on Sina Weibo, which stands as China’s largest social media platform. Through a comparative analysis encompassing the network’s structure, the growth rate and the duration of active fans, we delve into the influence wielded by six distinct thematic categories, endorsement, variety, public welfare, sports, music and national affairs. This analysis covers a cohort of nine celebrities spanning five diverse domains, including actors, singers, online influencers, anchors and athletes. The growth trajectory and life cycle exhibited by celebrity fans exhibit notable variations, both within and across the aforementioned themes. These dynamics are further influenced by the inherent structural attributes of the personal fan network belonging to each celebrity. Employing the K-Shape time series clustering algorithm, we have undertaken an in-depth exploration of outburst growth patterns observed in active fans and determined the optimal value of the number of clusters to be k=4 through comparative analysis. Our findings underscore that the themes of endorsement and public welfare exhibit all four growth patterns, namely Double-Peak, Oscillatory, Single-Peak and Continuous Growth Patterns. In contrast, when considering all themes collectively, they collectively demonstrate a single-peaked decaying growth pattern the insights gleaned from this study not only serve as a valuable reference and guide for celebrities across diverse domains who aspire to bolster and augment their social influence but also contribute to the burgeoning fan economy. Moreover, this research introduces novel perspectives and insights for scrutinizing patterns of fan growth and their corresponding dynamics.

Keywords: Social network; big data; Sina Weibo; K-Shape time-series clustering (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1142/S0129183124420038

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