微博签到大数据中旅游景区客流波动特征分析——以南京市钟山风景名胜区为例

Characteristics of Tourists Flow in Scenic Spots Based on Weibo Check-in Big Data:A Case Study of Zhongshan Scenic Spot in Nanjing City

基于微观尺度利用微博签到数据对旅游流进行研究。选取典型旅游风景名胜区钟山作为微观尺度景区内部旅游流研究代表,从信息时代下的虚拟网络视角入手,借用新浪微博平台,抓取相关微博大数据,结合时间分层法、经验模态分解法(EMD)对旅游区内部客流波动特征进行探索,并通过剥离节假日与工作日的方式,对不同属性的游客进行节日与节事效应差异的研究。发现钟山风景区不同类型游客均具有'M'型签到时间规律,但性别、地域属性不同表现出明显的签到周期波动差异。此外,节假日效应对不同属性游客的影响各不相同。

From the micro perspective, this paper, based on the platform of Sina Weibo, which selects Zhongshan scenic spot to research the tourist flow and captures related big data on Weibo, combines the methods of time stratification,Empirical Mode Decomposition(EMD), Kernel Density to examine tourists’ flow fluctuation characteristics in scenic spots and analyze the differences of holiday and festival effects among tourist segments. It is found that it shows the 'M' distribution of Weibo check-in time between different type of tourists in Zhongshan scenic spot and obvious difference of check-in periodic fluctuation between the gender and the different region, holiday effect has different effect on tourists.