The travel notes contain a wealth of tourists' behavior information, which provides a new way to study tourists' preferences. How to mine the text of online travel notes accurately and efficiently has become the key to research tourists' preferences. In this paper, the theory and technology of text mining were introduced into the research of tourists' preference through a large number of online travel notes accumulated on the Internet. The main research work of this paper was as follows: (1) The tourists' preference model was constructed by complex network method; (2) The travel notes data of Sanya tourists as an example was crawled and analyzed. In this paper, the theory of network travel data and text mining is introduced into the study of tourists' preferences, which not only improves the data quality of traditional preference research field, but also provides a new method for mastering tourists' preferences more accurately.