Satisfaction Analysis and Optimization of the Management of the Forbidden City in Beijing Based on Online Reviews

With the rapid development of the Internet and social media, public opinions and evaluations have been widely spread in cyberspace. As an important form of user feedback, online comments play a vital role in improving services and products. This study aims to evaluate tourists' satisfaction with the management of the Beijing Palace Museum scenic area by analyzing online comment data and to propose management optimization suggestions based on these findings. A large number of user comments from multiple online travel platforms and social media were collected through web crawler technology, and data were processed using text mining and sentiment analysis methods to identify key factors of tourist satisfaction. Research has found that tourists show varying degrees of satisfaction and dissatisfaction with the cultural heritage protection, tourism environment, service facilities, navigation system, and shopping and dining ex-perience of the Forbidden City. Based on these findings, this study proposes a series of optimization measures, including improving the tourist diversion mechanism, strengthening service personnel training, enhancing the moder-ni-zation level of facilities, enriching digital navigation content, and optimizing tourist experience design. In addition, the study also emphasizes the application prospects of big data and artificial intelligence technology in scenic area man-agement, in order to provide reference and inspiration for the management of the Forbidden City and other historical and cultural scenic areas. The con-clu-sions of this study contribute to promoting the sustainable development of the Forbidden City scenic area, improving tourist satisfaction, and enhancing its international competitiveness