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Article

Understanding the Impact of User Engagement Metrics on the Dissemination of Traditional Culture: A Structural Equation Modeling Analysis of Cantonese Opera Videos on Bilibili

1
School of Fine Arts, South China Normal University, Guangzhou 510631, China
2
School of Games & Creative Technology, University for the Creative Arts, Farnham GU97DS, UK
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Appl. Sci. 2025, 15(21), 11335; https://doi.org/10.3390/app152111335
Submission received: 8 September 2025 / Revised: 20 October 2025 / Accepted: 21 October 2025 / Published: 22 October 2025
(This article belongs to the Special Issue Advances and Applications of Complex Data Analysis and Computing)

Abstract

This study explores the dissemination of Cantonese Opera on Bilibili, a social media platform popular among younger audiences in China, as traditional cultural forms struggle to captivate younger generations. Platforms like Bilibili present opportunities for revitalizing interest in intangible heritage. This research aims to uncover how user engagement metrics influence the visibility and spread of Cantonese Opera content, providing insights for enhancing heritage promotion. Data were collected from 1916 Cantonese Opera videos using Python-based web scraping, focusing on eight user engagement metrics: Likes, Shares, Coins, Comments, Bullet Comments, Fans, Collects, and Plays. In addition to descriptive statistics, exploratory data analyses—including distributional assessment, correlation analysis, and K-means clustering—were conducted to examine engagement heterogeneity and interaction patterns across videos. The structural equation modeling (SEM) was employed to analyze the relationships among these metrics and their impact on content dissemination. Results show that Coins and Likes significantly predict Comments and Shares, indicating the importance of both monetary and non-monetary support in fostering interaction. The clustering results revealed three distinct video groups—high, moderate, and low engagement—demonstrating a long-tail pattern typical of social media visibility. Collects and Shares notably increase Plays counts, underscoring the role of curation and social diffusion. However, the negative impact of Coins on Plays reveals complex user motivations. These multi-level analyses provide a comprehensive understanding of engagement mechanisms and heterogeneity. They contribute to understanding the promotion of traditional cultural content through youth-oriented social media and offer practical implications for content creators and cultural institutions leveraging digital media for cultural preservation.
Keywords: Cantonese Opera; Bilibili; user engagement metrics; structural equation model; social media dissemination; intangible cultural heritage promotion Cantonese Opera; Bilibili; user engagement metrics; structural equation model; social media dissemination; intangible cultural heritage promotion

Share and Cite

MDPI and ACS Style

Cen, C.; Hu, J.; Zhang, Z.; Peng, H.; Jiang, T.; Luo, G. Understanding the Impact of User Engagement Metrics on the Dissemination of Traditional Culture: A Structural Equation Modeling Analysis of Cantonese Opera Videos on Bilibili. Appl. Sci. 2025, 15, 11335. https://doi.org/10.3390/app152111335

AMA Style

Cen C, Hu J, Zhang Z, Peng H, Jiang T, Luo G. Understanding the Impact of User Engagement Metrics on the Dissemination of Traditional Culture: A Structural Equation Modeling Analysis of Cantonese Opera Videos on Bilibili. Applied Sciences. 2025; 15(21):11335. https://doi.org/10.3390/app152111335

Chicago/Turabian Style

Cen, Chenghong, Jiaqi Hu, Zhuoxian Zhang, Hairong Peng, Tan Jiang, and Guang Luo. 2025. "Understanding the Impact of User Engagement Metrics on the Dissemination of Traditional Culture: A Structural Equation Modeling Analysis of Cantonese Opera Videos on Bilibili" Applied Sciences 15, no. 21: 11335. https://doi.org/10.3390/app152111335

APA Style

Cen, C., Hu, J., Zhang, Z., Peng, H., Jiang, T., & Luo, G. (2025). Understanding the Impact of User Engagement Metrics on the Dissemination of Traditional Culture: A Structural Equation Modeling Analysis of Cantonese Opera Videos on Bilibili. Applied Sciences, 15(21), 11335. https://doi.org/10.3390/app152111335

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