A Multidimensional AI-powered Framework for Analyzing Tourist Perception in Historic Urban Quarters: A Case Study in Shanghai
2025-09-05
Summary
The article discusses a multidimensional AI-powered framework developed to analyze tourists' perceptions of historic urban quarters using social media data, with Shanghai as a case study. The framework integrates visual analysis through semantic segmentation, color theme comparison, and sentiment analysis from tourist reviews to assess tourist satisfaction in areas like the built environment, service facilities, and business formats. This approach highlights the potential gaps between tourists' visual expectations and the actual urban landscape, offering insights into urban planning and heritage conservation.
Why This Matters
Understanding tourists' perceptions of historic urban areas is crucial for sustainable urban planning and enhancing visitor experiences. This study provides a comprehensive, data-driven approach to capturing these perceptions, which can inform decisions in tourism management and urban design. By identifying aesthetic preferences and emotional responses, city planners can better align urban environments with public expectations and cultural heritage values.
How You Can Use This Info
Professionals in urban planning, tourism, and heritage conservation can use this framework to gain insights into visitor satisfaction and aesthetic preferences. The findings can help tailor urban spaces to meet tourist expectations, guide investment in public amenities, and support the preservation of cultural identity. Additionally, leveraging AI-driven analysis can enhance strategic planning and marketing efforts by aligning them with actual tourist perceptions and experiences.