Research of the distribution of tourists' attributes based on internet data: A case study of Kunming

摘要

With the development of the era of big data, the ever-growing user trajectory provides the basis for studying multi-scale tourist activity law. This paper selected 17 famous tourist attractions in Kunming. Sina Microblog, Ctrip Travel, Lvmama Travel Network and other platforms were used to extract 139727 records between Oct. 2015 and Sep. 2016. The methods of data mining and clustering analysis were used to explore the activity characteristics of tourists with different attributes in scenic spot and the activity differences of different age tourists in different scenic spots affected by season, not only considered gender, geographical, check-in time and other factors, but also the introduced age attributes. At the same time, the scenic area is divided into "Adolescent active pattern ","Young and middle-aged women active pattern"," Middle-aged and old men active pattern" and " General active pattern" according to different tourists' activities law of different gender and age in spatial perspective. Research shows that female tourists are mainly distributed in the Green Lake Park, Nanping Street, Dounan Flower Market and other attractions, elderly male tourists are mainly distributed in Expo Park, Jindian area. Foreign tourists accounted for 86.32% of the total tourists, reflecting the rapid development of tourism in Kunming. The spatial distribution of tourist attractions has an impact on the distribution of tourists' attributes. The number of tourists of Shilin, Jiuxiang, Guandu Ancient Town are accounted for 36.38% of the total tourists, which shows that the spatial distribution of tourist attributes is consistent with the development of key tourist areas in Kunming.