上海旅游兴趣点搜索与点评热度空间格局及其耦合性研究

发布时间：2018-01-14 04:21

本文关键词：上海旅游兴趣点搜索与点评热度空间格局及其耦合性研究　出处：《上海师范大学》2017年硕士论文　论文类型：学位论文

【摘要】：随着旅游出行成为国民日常生活的重要组成部分,旅游业在国民经济中的地位进一步凸显。上海作为国际化大都市,优秀旅游目的地形象愈发鲜明,旅游整体空间结构基本形成。以互联网媒体平台为主流的网络信息日益成为影响旅游者出游的重要因素,旅游者通过游后点评、游记带来了不可小觑网络口碑效应,同时这些社交媒体中包含大量游客出行相关的POI数据,为研究旅游空间结构提供了新的视角,网络爬虫技术也为获得这些海量信息提供了技术支撑。本文在国内外旅游空间结构研究的基础上,以上海225个旅游兴趣点为研究对象,基于百度指数、大众点评平台,采用GIS、Geo Da空间分析方法和数理统计方法,开展二元数据支持下的旅游搜索热度空间格局与点评热度空间格局耦合性研究,探讨搜索与点评空间格局两者之间的关系及其影响因素。得出以下结论:(1)上海市旅游兴趣点搜索热度具有明显的极化特征,形成“一个中心旅游圈层”、“四个旅游片区、三个散点”的发展格局。不同区县旅游兴趣点搜索热度差异显著,浦东新区搜索热度最高,普陀区、静安区、虹口区、奉贤区、崇明区搜索热度较低。旅游兴趣点级别与搜索热度呈高度正相关,随着旅游兴趣点级别由高到低,同级别搜索热度差异逐渐减小,少部分低级别旅游兴趣点,如田子坊在百度搜索拦上频率相对较高,搜索热度高于一些高级别旅游兴趣点。游客对上海特色街区与街巷、主题乐园、动物与植物展示地显示出了较大的兴趣,对休闲场馆、城市公园、名人故居、宗教场所保持着很低的兴趣水平。(2)上海旅游兴趣点的点评热度与搜索热度相比较,具有更为明显的空间分布差异,旅游兴趣点点评热度之间的差异程度较大。点评热度呈现“一核、多心”的空间发展格局,与搜索热度格局相比较,中心旅游圈层的范围变大,基本囊括整个上海中心城区乃至延伸到闵行区西北。上海16个区县的点评热度差异程度不明显,黄浦区、长宁区等评分高于平均水平,静安区、普陀区、闵行区、松江区、宝山区等评分低于平均水平。四级旅游兴趣点的评分均值达到最高,在第四等级之后旅游兴趣点的评分之间的差异程度随着等级的降低逐步减少。游客对上海休闲场馆、特色街区与街巷、名人故居、宗教场所、主题乐园保持着好评的态度,城市公园、动物与植物展示地持着较差评的态度。(3)旅游兴趣点搜索热度空间格局与点评热度空间格局有一定的相似性又有明显的差异性。重心均位于徐汇区的东北方向,均呈集聚分布,搜索空间分布标准差椭圆的面积小于点评热度空间分布标准差椭圆。根据Geo Da进行的双变量局部空间自相关分析,得出高搜索—高点评型旅游兴趣点44个,低搜索—高点评型旅游兴趣点101个,高搜索—低点评类型4个,低搜索—低点评型旅游兴趣点10个。(4)通过对每一种类型的兴趣点评论进行内容分析,提炼影响评分的重要因素,结合旅游目的地竞争力评价指标体系的基础上,初步构建旅游兴趣点网络内容分析体系,采用李克特五级量表对高搜索—低点评型的网友评论内容进行编码打分,将高搜索—低点评型指标得分与百度指数进行SPSS相关性分析,得出影响两者之间的显著因素有资源丰度、区位地位、周边环境、性价比、工作人员服务、垃圾处理设施、交通设施。(5)最后,根据上海市搜索热度空间格局与点评热度空间格局特征、两者之间的影响因素,提出关于高搜索—低点评旅游兴趣点的三条发展优化策略:提升工作人员整体素质与服务态度、营造良好优美的旅游公共服务环境、打造魅力丰富的鲜明旅游品牌形象。
[Abstract]:With travel has become an important part of people's daily life, the role of tourism industry in the national economy is further highlighted. Shanghai as an international metropolis, excellent tourism destination image more vivid, overall tourism spatial structure is basically formed. By the Internet media platform for mainstream network information is becoming an important factor affecting tourist travel, tourists through travel reviews, travel has brought significant word-of-mouth effect, at the same time these social media contains a large number of tourists travel related POI data, to study the spatial structure of tourism provides a new perspective, the web crawler technology also provides technical support for these vast amounts of information. Based on the domestic and foreign Research on the spatial structure of tourism in Shanghai, 225 points of interest in tourism as the research object, based on the Baidu index, the public comment platform, using GIS Geo, Da space Analysis method and mathematical statistics method, carry out the two metadata under the support of the tourism research of spatial pattern and heat pattern coupling heat comment space search, explore the relationship between the two factors and comments on the search space pattern and its influence. Draw the following conclusions: (1) Shanghai city tourism interest point search heat with polarization characteristics, forming a "a center of tourism circle", "four area tourism development pattern and three spot. Different county tourism interest point search heat difference, Pudong New Area search Putuo District, Jingan District, the highest heat, Hongkou District, Fengxian District, Chongming area search heat low. Tourism interest level was positively correlated with the search with the heat. Tourism interest points from high level to low level, the same search heat difference decreases gradually, a few low level tourism points of interest, such as Tianzifang in the Baidu search stopped on the relative frequency High search heat higher than some high level tourism interest. Visitors to the streets and alleys, the characteristics of Shanghai theme park, animal and plant display to show the great interest of leisure venues, city parks, celebrities, religious sites maintained a very low level of interest. (2) Shanghai tourism point of interest comment on heat and heat search compared with more spatial distribution differences between the tourism interest difference greatly. Heat comment comment is "a suspicious nuclear heat," the spatial development pattern, compared with search heat pattern, center of tourism becomes large, basically encompasses the entire Shanghai city center and extending to the northwest of Minhang District. The degree of heat difference comments on 16 counties of Shanghai is not obvious, Huangpu District, Changning District score is higher than the average level, Jingan District, Putuo District, Minhang District, Songjiang District, Baoshan District and other. Four points below the average level. The mean score of tourist interest reached the highest in the fourth grade after the difference degree between tourism interest point score with the level decreased gradually reduced. Visitors to the Shanghai leisure venues, neighborhood characteristics and streets, celebrities, religious sites, theme park maintained a city park, praise attitude animal and plant display their poor rating attitude. (3) tourism interest point search heat spatial pattern and spatial pattern of heat comments have some similarities and differences. The north east direction of center are located in Xuhui District, showed a clumped distribution, search space distribution of standard deviation ellipse area is less than the distribution of comments standard deviation ellipse heat space. According to the double variable Geo Da local spatial autocorrelation analysis, the high - high rated tourist search 44 points of interest, low - high tourism search comments 101 points of interest, high - low reviews 4 types of search, search and evaluation of tourism low lows 10 points of interest. (4) the content of each type of interest point critical analysis, refining the important factors influencing the score, based on index system of tourism destination competitiveness evaluation, preliminary construction tourism interest network content analysis system, using the Likert five scale encoding scoring for comment content search - low rating type, high - low rating index search Baidu index score and SPSS correlation analysis, the impact of significant factors between resource abundance, geographical position, surrounding environment, price, staff services, waste disposal facilities, transportation facilities (5). Finally, according to the features of heat spatial pattern and spatial pattern of heat comment search Shanghai City, between the two factors, put forward a high. The three development optimization strategies of cable low comment tourism interest points are to enhance the overall quality and service attitude of staff, create a beautiful and beautiful tourism public service environment, and create attractive and colorful tourism brand image.

【学位授予单位】：上海师范大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F592.7

【参考文献】