| In the era of big data,the role of network information in tourism decisions-making is gradually increasing.Before making tourism decisions,tourists usually use the Internet to search for a series of tourism destination information.This search trace reflects tourists’ attention to the tourist destination.Fangchenggang has unique seaside mountain tourism resources and advantageous geographical location.It is the only city in my country connected to ASEAN by sea,land and river.It is also one of the first two border tourism pilot areas established in my country.The paper takes Fangchenggang as a case to analyze the spatiotemporal distribution characteristics and influencing factors of the network attention of border tourism destination,so as to provide a reference for Fangchenggang border tourism destination network marketing,source market development and traffic forecasting.Through the Baidu index platform,with “Fangchenggang Tourism” and“Fangchenggang Tourist Attractions” as superimposed keywords,collecting daily network attention data of Fangchenggang tourism from 2011 to 2020.Based on Arc GIS spatial analysis method,correlation analysis method,and geographic detector analysis method,using the inter-annual variation index,coefficient of variation,Moran index to analyze the spatiotemporal distribution characteristics and influencing factors of Fangchenggang tourism network attention.The conclusions are as follows:(1)Time distribution characteristics: First of all,from the characteristics of inter-annual variation,the overall national attention to Fangchenggang tourism network is on the rise,and the inter-annual changes are relatively large.Secondly,from the perspective of seasonal changes,the seasonal differences are obvious,the summit period is mainly concentrated in summer and autumn,and the winter is mostly the trough period.Then,from the perspective of characteristics of the weekly period,network attention on weekdays is generally higher than on weekends.Finally,from the perspective of holiday characteristics,network attention continued to rise in the first three days of May 1st,and reaches the peak on the day before or on the day;during the National Day period,the peak of network attention usually appears on the second or third day of the holiday.On the whole,the network attention gradually tends to be evenly distributed during the Golden Week.(2)Spatial distribution characteristics: From overall view,various provinces have great differences in the network attention to the border tourism destination of Fangchenggang.Guangxi and its surrounding provinces and the developed eastern coastal provinces pay more attention to Fangchenggang tourism,and the economically backward western provinces pay less attention to Fangchenggang tourism.From a regional perspective,the difference in network attention is greatest in the western region,followed by the eastern region,then the central region,and finally the northeast region.In addition,Fangchenggang tourism network attention has obvious spatial agglomeration,the vast majority of provinces fall into the first and third quadrants,showing a “high-high” and “low-low” distribution pattern.(3)Influencing factors of temporal and spatial distribution characteristics: In terms of time distribution influencing factors,the article mainly selects climate comfort and leisure time as measurement indicators.The study found that leisure time is the main factors affecting the time distribution characteristics of Fangchenggang tourism network attention.From the perspective of spatial distribution factors,the economic linkage factors between the two places have the greatest impact on the network attention of Fangchenggang border tourist destination;followed by regional economic development level factors;followed by population size factors and geographic location factors;then education level factors and age structure Factors;the least influential factor is the degree of Internet development.Based on the above analysis,the article puts forward corresponding countermeasures for Fangchenggang tourism network marketing: digging deeply tourism big data;implementing time-space differentiated marketing strategies;adopting search engine marketing strategy;strengthening mobile phone mobile terminal network marketing;cultivating professionals in tourism network marketing. |