A Study On The Attention Of Scenic Spots And The Analysis Of Tourists' Emotion Based On The Crowdsourcing Geospatial Data

In recent years,with the increasing living standards of our residents,China has gradually entered the era of national tourism.Hangzhou West Lake Scenic Area,as a famous 5 A-class scenic spot in China,has a high visibility in the world,and the healthy development and management of its tourism market is of great significance to the construction of local and even regional tourism image.In the context of the increasing integration of the Internet into the tourism industry,social media brings together a large number of Crowdsourcing Geospatial Data suitable for analyzing the needs of tourists,can provide big data support for the image promotion and management optimization of tourist attractions.This study uses big data technology to crawl visitor locations and related comment text data by calling the Weibo API(Application Programming Interface,application programming Interface)and using professional crawler software on Sina Weibo and Ctrip,this builds a database based on Crowdsourcing Geospatial Data.Based on the spatial information and text information of the Crowdsourcing Geospatial Data,the nuclear density analysis and emotion analysis model are used to analyze the visitors ' attention to the scenic spot and the time dynamics and spatial distribution characteristics of the emotion change,and the factors affecting the tourist image of Hangzhou West Lake Scenic area are found through the topic clustering analysis of the scenic spot review.Then,combined with the actual situation of West Lake Scenic Area,the relevant countermeasures and suggestions are put forward for the sustainable development of Hangzhou West Lake Scenic Area,in order to provide scientific decision-making basis for improving the network image of Hangzhou tourism,promoting the health and sustainable development of tourism,and can provide a good reference for big data analysis to serve the reform of scenic Area management.The main research results include:Firstly,based on the tourist spatial information data,the nuclear density analysis method is used to analyze the spatial distribution characteristics of tourists in the whole Hangzhou scenic area at different spatial scales.The hot spots with high tourist attention show the characteristics of scenic spots as the core,scattered along the edges of other scenic spots and trunk roads,and the main gathering points of tourists are distributed within 5 km of the central Lake Scenic Area,and the range of scenic spots corresponding to the number of tourist Weibo released by the time cycle of the year,month and day is found Since 2015,the network attention of scenic spots has increased at an annual rate of about 40%,and at the time scale of the month and day,the change of tourist attention is mainly related to tourism demand,season and rest law,and shows a strong seasonality,the attention of tourists is more than spring and autumn than winter and summer,the day is higher than the night From the domestic and foreign tourism market,the change of the attention degree of scenic spot is proportional to the economic and traffic development of the source.Secondly,on the basis of emotional dictionary,the emotional value of visitor comment content is obtained according to the emotional analysis model,and then the comment content is analyzed in depth from different time and space scale.From the month,season and daily average,the fluctuation of the emotional mean of tourists,mainly the seasonal and diurnal alternation factor dominates the mood change of tourists,from the spatial scale of the source,in the fourth level of Inner Mongolia,Gansu province as the representative of the Northwest Territories and Shandong Province,The emotional mean of the northern region represented by Beijing is higher than the overall emotional mean,while the other levels are close to or below the overall emotional mean level,mainly because of the comfortable and pleasant climate environment and the unique natural and cultural landscape of the scenic spot,which exceeds their psychological expectations compared with the northern tourists with large differences in living environment.;Other levels of the region are affected by travel costs or by the high expectations of re-visit to lower the regional emotional mean.Finally,through the topic clustering from the positive and negative aspects of the impact of Hangzhou West Lake Scenic Area tourism image factors,including through word frequency analysis,it is concluded that visitors to Hangzhou West Lake positive Cognitive image concentrated in the natural environment,humanistic history and cultural background,tourism facilities and urban image and so on;The negative factors mainly focus on the internal infrastructure of scenic spots,service quality,management mode and weather conditions and other factors.On this basis,in view of the specific existing problems,from the inside and outside of the scenic area,the improvement of the tourist image of scenic spots put forward some practical suggestions.Mainly include: for the interior of scenic spots,we should improve the tourist service facilities,improve the quality of scenic service personnel,and provide fine and humanized services for different types of tourists;for the whole city,we should establish cooperation mechanism with relevant departments,control various traffic problems,do a good job in Hangzhou air quality control and supervision work,Do a good job of network information feedback work,but also according to the generally reflected problems of tourists to respond in a timely manner,to maintain a good overall image of the tourist landscape.This paper analyzes the Crowdsourcing Geospatial Data with various attribute information through multi-angle analysis,provides the support of relevant data for the exploration of the future development mode of Hangzhou West Lake Scenic Area and the planning of tourism market,realizes the rational allocation of tourist resources in scenic spots as a whole,develops the potential market of tourism,and improves the attention and satisfaction of tourist tourism.Thus,it provides a new way of thinking for the study of tourism geography centered on the Crowdsourcing Geospatial Data.