Revitalizing Shadow Puppetry through Data-Driven Insights: An LDA-Sentiment Fusion Approach for Cultural Product Innovation

This study proposes a method that integrates e-commerce big data and user requirement analysis to address the issues of a lack of systematic analysis of real-time user feedback data in the active inheritance of intangible cultural heritage. Research Method: Firstly, web crawling technology is used to obtain online review data of products from online platforms. After preprocessing through word segmentation technology, the LDA model is used to extract the perceived topic classification of online review text data, and a semantic network of high-frequency words is constructed. Finally, the dimensional structure of the perceived value of products is analyzed and verified through questionnaire surveys. Research has found that: (1) the three-dimensional structure of "technical precision - functional adaptation - cultural identity" in the demands of shadow puppetry cultural and creative users; (2) the demand dimension presents a dual-core driving feature of "Children's practice orientation" and "Priority of craftsmanship experience"; (3) Form six major thematic clusters including craft aesthetics, easy to operate, and interactive experience, etc. Based on this, this article innovatively proposes a three-dimensional collaborative design path of "symbol-narrative-interaction", effectively solving the contradiction between symbol transplantation and cultural decoupling in the modern reinterpretation of traditional skills. This method provides a dynamic demand analysis mechanism for the active inheritance of intangible cultural heritage. It has innovative value in both cultural heritage user demand theory and cultural creative industry practice.