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作 者:罗明春[1] 谌战飞 LUO Mingchun;CHEN Zhanfei(School of Tourism,Central South University of Forestry and Technology,Changsha Hunan 410004,China)
机构地区:[1]中南林业科技大学旅游学院,湖南长沙410004
出 处:《长沙大学学报》2023年第4期51-59,共9页Journal of Changsha University
摘 要:岳麓山-橘子洲景区是长沙著名景点之一,是长沙旅游的风向标。以景区相应关键词的百度指数为网络关注度计算基础,分析景区2018—2021年国内网络关注度时空分布规律及变化特征。结果显示,景区网络关注度总体处于上升趋势,2020年虽有较大幅度下跌,但2021年强势反弹,扭转了下跌势头。这4年间景区国内网络关注度时序规律变化总体不大,各年际变动相对较小,各季节占比保持了相对均衡,但是2020年后景区网络关注度淡、平、旺季分布规律有明显改变,假期分布规律在2020年上半年有较大变化。地理集中指数显示景区网络关注度空间分布相对分散,各省区市网络关注度变化相对同步,但首位度指数显示湖南本省优势突出,省域变异系数表明各省区市之间差异较大,自相关分析结果显示空间分布有较强集聚性,影响因素分析结果表明地理空间距离、人口数量和GDP等与景区网络关注度之间存在较强相关性。Being a famous tourist attraction of Changsha,Mount Yuelu-Orange Isle is the indicator of tourist volume in this city.This paper analyzes the spatiotemporal distribution of its domestic online attention during 2018-2021,whose calculation is based on the Baidu searching index of relevant keywords.Analyzing result shows that the online attention of this tourist attraction is still on a rising tract.Although it did plummet in 2020,the rebound in 2021 is strong enough to reverse that downward trend.The temporal distribution of its online attention experienced only small changes in this period.Its annul changes are moderate and its seasonal distributions are balanced and stable.However,the monthly distribution of off,flat and peak seasons has changed significantly since 2020,and its holiday distribution curves were flattened in the first half of 2020.The geo-concentration indexes show that spatial distribution pattern is dispersive in general and changes of provinces(autonomous regions and municipalities)are synchronous to some extent,while its primacy degree indexes show that the advantage in its primary province is too large.Variation indexes reflect that discrepancies among different provinces(autonomous regions and municipalities)are large.Spatial autocorrelation analysis shows a strong aggregation tendency in its spatial distribution.Affecting factors analysis shows that online attention of each province is closely related to its spatial distance,residential population number and GDP.
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