Abstract
This paper takes Gongtan Ancient Town of Chongqing as a case study, takes the online comment text of tourists on the websites of Ctrip and Dianping as data, analyzes the online text through content analysis, and uses ROST CM-6 software to conduct word frequency, emotion and semantic network analysis, aiming to deeply explore the tourist experience of Gongtan Ancient Town. The results show that: (1) Tourists' experience of Gongtan Ancient Town consists of five dimensions: tourist destination perception, sensory experience, physical and mental experience, tourist destination characteristic experience and service experience. (2) Natural scenery, local characteristics and service guarantee are the main tourist attractions of Gongtan Ancient Town.(3) Tourists' overall experience and perception of tourism in Gongtan Ancient Town tend to be positive emotions. Tourists' dissatisfaction mainly comes from heavy traffic jams during holidays, poor service attitude of staff and poor accommodation conditions. (4) The semantic network is divided into three levels: the core area is the tourists' objective cognition of the scenic spot name and location; The sub-core circle is the cultural cognition of the ancient town and the characteristic architecture and activity projects; The edge layer is the image characteristic cognition and tourism evaluation of the ancient town. In addition, some optimization suggestions are put forward for the existing problems of Gongtan Ancient Town. The research results not only provide a scientific basis for the tourism development and construction of Gongtan Ancient town, but also provide a reference for the optimization of tourist experience in other ancient towns.
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