Island tourism is an important part of the development of the marine economy. Understanding the tourist experience of island tourism is conducive to promoting the development of marine tourism. This study takes the main island tourism attractions in Jiangmen, China, as a case, and analyzes the tourist experience of island tourism through a text mining method based on the text reviews of tourists on Ctrip. The study shows that beach, hotel, attraction, seafood and seawater are the main discourse system core of tourists’ evaluation of island tourism. Tourists’ sentiment evaluation of island tourism is generally positive. Nice, convenient, clean, cheap and comfortable are the main sentiment characteristic words of tourists. The results of LDA topic model analysis show that tourists island tourism experience is mainly divided into four categories: coastal scenery, seafood cuisine, beach environment and entrance service.

In order to analyse the factors and dimensions that customers pay attention to smart hotels, this experiment selects the user reviews of five smart hotels on Ctrip as the research samples, and carries out network text big data collection, text pre-processing and topic mining through the relevant algorithms of Python programming language. The results show that customers’ accommodation experience of smart hotel mainly includes five aspects: breakfast and transportation, staff service level, intelligent service, room environment, and room hardware facilities. Among them, the customer’s attention to the intelligent services of smart hotels and the intelligentization of hardware facilities in guest rooms reflect the difference in customer experience between smart hotels and traditional hotels, which provides a certain reference for the optimization of hotel service levels.