机构地区:[1]河南大学地理与环境学院,开封475004 [2]河南大学区域发展与规划研究中心,开封475004 [3]河南大学环境与规划国家级实验教学示范中心,开封475004
出 处:《湖南师范大学自然科学学报》2024年第6期34-43,共10页Journal of Natural Science of Hunan Normal University
基 金:国家自然科学基金项目(42271213,2301237);河南大学研究生教育教学改革研究与实践项目(YJSJG2022XJ028);河南大学研究生培养创新与质量提升行动计划项目(SYLKC2022003);河南大学研究生教育创新与质量提升工程项目(SYLYC2023015)。
摘 要:基于搜索引擎、社交媒体、旅游网站与短视频指标数据构建评价体系,运用位序—规模、核密度、类型划分等方法来剖析湖南省红色经典景区综合网络关注度的等级类型、空间差异特征及其驱动力因素。研究结果表明:(1)从位序—规模法则看,整体为非均衡结构,其中高位序景区发育水平高且具显著优势,而中、低位序景区发育不足且具层次性。(2)从空间分异格局看,高关注景区集中分布于长沙与湘潭,且以岳麓山和毛泽东故居为核心形成了较密集的高值集聚区;从子系统看,搜索引擎、旅游网站与短视频子系统与整体类似,而社交媒体子系统相差较大。(3)从空间集聚状态看,综合系统中的高、低水平区呈显著集聚态势,而中等区则趋于随机分布;从子系统看,搜索引擎、社交媒体、短视频子系统与整体相比差异较大,旅游网站子系统相似。(4)从类型划分看,高品质景区的关注度与其基础实力的匹配性较差,中等品质区的关注度整体较低;低品质区有“高关注”与“低关注”两种类型。从贡献度看,搜索引擎对景区网络宣传效果的贡献率较高,社交媒体与旅游网站的推广成效较弱,短视频仅对高、低关注型景区的贡献较大。(5)从虚实对比看,隶属长沙的红色景区在虚拟网络和实体空间中均具领先优势,其中虚拟关注度在长沙和湘潭形成了“一主一副”的两处高值区,而实体关注高水平区仅在长沙集聚分布。(6)从影响因素看,主要因子为景区基础实力、区域教育水平与网络化普及程度,次要因子为地区经济实力、交通优势度以及红色资源禀赋,一般作用因子有城市发展水平、政府支持力度以及人口规模等。This paper constructed an evaluation system based on search engine index,social media index,tourism website index and short video index,by using the rank-size model,kernel density estimation,spatial classification and other methods to analyze the spatial pattern and influencing factors of red scenic spots in Hunan province.The results show as follows.(1)From the perspective of the rank-size model,it shows obvious advantages in the high-rank red scenic spots,but the middle-rank and low-rank scenic spots are underdeveloped and show larger difference in terms of the network attention.(2)From the perspective of spatial pattern,high-attention scenic areas are concentrated in Changsha city and Xiangtan city,forming a relatively dense high-value aggregation zone centered around Yuelu Mountain and the former residence of Mao Zedong.In terms of subsystems,the subsystems of the search engine,travel website,and short video subsystems are similar to the comprehensive system,while the social media subsystem shows significant differences.(3)From the perspective of spatial aggregation,the comprehensive system of spots show a significant clustering pattern of high and low-level areas,while the medium-level of spots tend to exhibit a random distribution.In terms of subsystems,there are considerable differences in the search engine,social media,and short video subsystems compared to the comprehensive system,while the travel website subsystem is more similar to it.(4)From the perspective of type classification,the attention received by high-quality spots does not match well with their underlying strengths,while network attention of medium-quality spots remains relatively low.Low-quality spots demonstrate two categories of high attention and low attention.In terms of contribution to enhance the level of network attention,the subsystem of search engine significantly enhances the online promotional effectiveness of spots,whereas the subsystems of social media and travel website show weaker promotional results.Short videos primarily co
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