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作 者:王娟[1] 孟凤娇 封洁洁 WANG Juan;MENG Fengjiao;FENG Jiejie(Management College of Ocean University of China, Qingdao 266100, China;Qingdao Vocational and Technical College of Hotel Management, Qingdao 266100, China)
机构地区:[1]中国海洋大学管理学院,山东青岛266100 [2]青岛酒店管理职业技术学院,山东青岛266100
出 处:《地域研究与开发》2022年第1期85-90,共6页Areal Research and Development
基 金:国家社会科学基金项目(20BJY199);山东省社会科学规划项目(19BYSJ20)。
摘 要:基于社交平台的旅游大数据能够反映旅游者出行过程中的移动轨迹,为旅游流研究提供丰富的数据来源和崭新的研究视角。对2011—2019年游客展现在穷游网上的成渝城市群16个城市的网络游记进行抓取和整理,并结合GIS空间分析、社会网络分析和地理探测器分析,动态刻画旅游者的空间移动演变轨迹,识别演化的影响因素和作用机理。结果表明:旅游客流以成都和重庆为双核心的空间极化现象显著且具有持久性,旅游客流的重心向东南方向偏移且呈现长半轴缩短、短半轴增长的趋势。在旅游客流节点-轴线特征方面,点的程度中心度、接近中心度和中介中心度绝对差异扩大,相对差异缩小;整体网络结构洞水平较低,效能值上升,约束值缩小;客流轴线指向由相对分散向相对集中转变,指向空间邻近城市的城市数量减少,指向核心城市和旅游资源禀赋较高的城市数量增加。旅游资源禀赋和旅游信息化水平两个因素对成渝城市群旅游客流空间格局的塑造和演化影响力值最大。Abundant tourism time-space information is contained on social media platform,which not only reflects tourists’moving trajectory,but also provides new angles for tourism big data research.This paper acquires tourists’travel notes and itineraries from online travel service platform QYER from 2011 to 2019 in Chengdu-Chongqing Urban Agglomeration by using Python 3.7 as data mining program to grab,extract,clean and categorize tourists flow data and construct directed matrix.This paper depicts tourists’spatial trajectory and identifies influential factors and functional mechanism with combined tools such as spatial analysis,social network analysis and geographical detector.Conclusions are drawn that the Chengdu-Chongqing dual core-based structure is evident and persisting.Tourist flow gravity center deflecting to southwest,long semi-axis shortened and short semi-axis lengthened.As to tourist flow network structure,degree centrality,closeness centrality and betweenness centrality’s absolute differences enlarged,relative difference shortened.Total network structure hole level is low,but efficiency value and constraint value are improved.Tourist flow more to core cities and high endowment cites rather than adjacent cities.In aspects of impacting factors,tourism resource endowments and information level contribute more to spatial structure formulation and evolution compared with tourism accommodation ability,service quality,transport accessibility.
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