On-the-Ground Application of Cloud Evaluation: Big Data Reveals Experiential Effectiveness of Industrial Heritage Revitalization

Post-occupancy evaluation is a critical mechanism for ensuring the sustained success and continuous improvement of industrial heritage revitalization initiatives. The quality of the visitor experience plays a key role in determining a project’s long-term vitality. This study focuses on assessing user satisfaction with a revitalized industrial heritage site by employing web crawling and data mining techniques to systematically collect and analyze user-generated reviews from major online platforms. Using the 1933 Old Millfun in Shanghai, China, as an example, this research identifies six core evaluation dimensions derived from extensive user commentary: project accessibility, cultural legibility, aesthetic distinctiveness, commercial appeal, facility completeness, and sense of security. These dimensions are integrated into a comprehensive analytical framework, with the Fuzzy Comprehensive Evaluation (FCE) method applied to quantitatively assess the site’s performance across each category. By combining qualitative sentiment data with quantitative evaluation techniques, the data-driven presentation provides nuanced insights into the evolving user experience. The research results contribute to the development of a replicable and scalable paradigm for measuring user experience in industrial heritage revitalization and highlights the potential of digital platforms as valuable tools for heritage site management and continuous optimization.