| Summary: | In the context of global warming, the development of the summer tourism industry has maintained a rising trend, and has gradually become a key area of widespread concern and continuous innovation by the government, tourism companies, scientific research, and the media. This paper takes domestic tourists who go to Changbai Mountain for summer travel as the research object, using the online travel notes of many travel websites such as Mafengwo and Ctrip as the data source, with the help of NLPIR big data semantic intelligent analysis platform, using text mining, network analysis, co-occurrence analysis and other methods to analyze the text data of travel notes quantitatively and qualitatively. The characteristics and laws of Changbai Mountain summer tourism consumer behavior are analyzed from three aspects: tourism decision-making behavior, tourism consumer preference, and post-tour evaluation.
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