Promotion of Preservation and Inheritance of Shanxi Pu Opera through Participatory Digital Platforms
Keywords:
Shanxi Pu Opera, participatory digital platforms, cultural preservation, user engagement, neural network analysisAbstract
Background and Aims: Shanxi Pu Opera, one of the oldest forms of traditional Chinese opera, is facing significant challenges in preservation and transmission due to globalization, modernization, and generational cultural gaps. This study aims to explore how participatory digital platforms can be utilized to support the sustainable preservation and cultural transmission of Shanxi Pu Opera. The research investigates user engagement patterns, platform component effectiveness, and technological contributions toward cultural heritage preservation.
Methodology: A quantitative survey was conducted with 200 participants who use or are familiar with digital platforms related to traditional culture. The research instrument was a structured questionnaire, tested for reliability and validity (Cronbach’s Alpha = 0.950, KMO = 0.955). Descriptive statistics, Pearson correlation analysis, and a Multi-Layer Perceptron Neural Network (MLPNN) model were used to analyze the data and assess relationships among platform features and perceived effectiveness in cultural preservation.
Results: The results indicate that key platform components including user interface and experience, content management, and technical architecture are significantly correlated with user engagement and perceived effectiveness. The MLPNN model demonstrated strong predictive performance, with AUC values ranging from 0.603 to 0.915. The most influential factors identified were technical scalability, content auditing, and user-centric design.
Conclusion: Participatory digital platforms show great potential in revitalizing traditional cultural practices such as Shanxi Pu Opera by attracting diverse users and enhancing cultural transmission. To strengthen cultural preservation efforts, future platform development should prioritize interactive features, content accuracy, and inclusive design. This study contributes valuable insights for digital heritage preservation and sets the groundwork for future interdisciplinary research in culture and technology.
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