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

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.

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Publication Details

Journal
Applied Sciences
Published
2025-10-22
DOI
https://doi.org/10.3390/app152111335
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
0.00

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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

Z H Zhang, Tan Jiang, Chenghong Cen, Luo Guang et al.
Applied Sciences
Digital Marketing and Social Media
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

Z H Zhang, Tan Jiang, Chenghong Cen, Luo Guang, Jiaqi Hu, Hairong Peng
article en

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.

Applied SciencesVol. 15(21)
South China Normal University (CN), University for the Creative Arts (GB)
National Office for Philosophy and Social Sciences
Openalex Percentile: Top 60%
Digital Marketing and Social Media
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