Study On Spatial Relationship Between Network Attention And Tourist Flow Of National Scenic Spots In Hunan Province

With the rapid integration and development of "Internet + tourism",the internet has become the main platform for people to release,transmit and obtain tourism information.Analysis of the time-space distribution characteristics of online search data of tourist destinations represented by online attention degree,and discuss the relationship between the online search data and the tourist quantity has an important role in the development of tourist attractions.This paper takes 23 scenic spots of Hunan province as the research objects and Collect online attention data of 2011 to 2017 based on Baidu index platform.Using the Gini Coefficient,the interannual variability index,Standard Deviation Ellipse method and Inverse Distance to a Power method to analysis space distribution pattern of the online attention degree and the tourist quantity.Then,a geographic weighted regression model was established to analyze the spatial changes of the relationship between the online attention degree,the tourism resources,degree of transportation convenience,the level of tourism economy and Tourism development level of Hunan national scenic spots.Conclusions include:1)The spatial distribution of online attention degree and spatial distribution of Hunan national scenic spots is highly concentrated,and the online attention is focused on these scenic spots: Fenghuang gucheng,Wulingyuan,Hengshan,Yueyang Lou-Dongting lake,Yuelu mountain;tourists are concentrated in the Wulingyuan,Hengshan,Fenghuang gucheng,Yuelu mountain,Shaoshan,Dehang.2)The spatial pattern of network attention and passenger flow in hunan province is obviously different.The network attention is trending from west to east,and the passenger flow pattern is trending from northwest to southeast.there are four kinds of correlation patterns: High attention--high flow,high attention – low flow,low attention – high flow,low attention – low flow.3)The geographic weighted regression model based on,tourist quantity,the tourism resource,the degree network attention degree of transportation convenience and tourism economic level can have good effect.These variables have a positive relationship with tourist quantity.The relationship between these variables and network attention degree is,from large to small,tourism economic level,tourism resource,network attention degree and degree of transportation convenience.4)In the model,the influence of various variables on the network attention of the same scenic spot is significantly different,and the effect of the same variable on different scenic spots is also significantly different.On the whole,the relationship between tourist flow and network attention shows the law of decreasing from western scenic spots to eastern scenic spots.