Research on Tourist Satisfaction Evaluation with Northeast Asia Royal Palace Based on Big Data

Tourist satisfaction is an important indicator for the survival and development of tourist attractions. The use of big data technology can provide a more scientific and objective understanding of tourists' needs and emotional changes, as well as valuable insights into studying their preferences and behaviors. This can help tourism organizations objectively and efficiently monitor tourist satisfaction and provide targeted strategies and suggestions for improving and enhancing it. Ultimately, this can lead to sustained, rapid, and healthy development of tourist attractions. In this research, with the help of Python technology, comment data from the top three Online Travel Agency (OTA) websites in China were collected, and the ROST Content Mining software was used to analyze the collected data. Word cloud map was used to display high-frequency words, aiming to evaluate the tourist satisfaction of three representative imperial palaces in Northeast Asia using big data technology. The research results show that the size and preservation degree of the palaces, cultural heritage value, and tourist interaction and communication modes are important factors influencing tourist satisfaction. Future research directions and suggestions for tourist satisfaction research are given from the perspective of deep integration of tourism market and consumer behavior research, as well as artificial intelligence technology.