地理科学进展 ›› 2014, Vol. 33 ›› Issue (11): 1462-1473.doi: 10.11820/dlkxjz.2014.11.004

• 旅游与文化地理 • 上一篇    下一篇

基于Tripadvisor 的中国旅游地国际关注度及空间格局

王琨1, 郭风华2, 李仁杰1,3, 傅学庆1,3   

  1. 1. 河北师范大学资源与环境科学学院, 石家庄 050024;
    2. 河北省科学院地理科学研究所, 石家庄 050011;
    3. 河北省环境演变与生态建设实验室, 石家庄 050024
  • 收稿日期:2014-04-01 修回日期:2014-07-01 出版日期:2014-11-25 发布日期:2014-11-25
  • 通讯作者: 李仁杰(1975-), 男, 河北鹿泉人, 教授, 博士, 研究方向为地理信息可视化与空间建模, E-mail:lrjgis@163.com E-mail:lrjgis@163.com
  • 作者简介:王琨(1988-), 女, 河北元氏人, 硕士研究生, 研究方向为旅游地理信息挖掘, E-mail:vickyohara1988@163.com
  • 基金资助:
    国家自然科学基金项目(41101105,41171105);河北省高校重点学科建设项目;河北省软科学研究计划项目(13406002D)

Tourism attention degree about China from overseas and its spatial patterns based on Tripadvisor

WANG Kun1, GUO Fenghua2, LI Renjie1,3, Fu Xueqing1,3   

  1. 1. College of Resource and Environment Science, Hebei Normal University, Shijiazhuang 050024, China;
    2. Institute of Geographical Sciences, Hebei Academy of Sciences, Shijiazhuang 050011, China;
    3. Hebei Key Laboratory of Environmental Change and Ecological Construction, Shijiazhuang 050024, China
  • Received:2014-04-01 Revised:2014-07-01 Online:2014-11-25 Published:2014-11-25

摘要: 用户贡献内容(UGC)已逐渐成为旅游行为与感知研究的重要数据源.区别于通常利用搜索引擎关键词数量描述网络关注度的方法,本文引入电子社区层次结构为权重因子,建立了基于社区UGC的旅游关注度模型,能够灵活调节模型表达的重点,优化计算结果.针对著名旅游电子社区Tripadvisor 的研究发现,国外社区用户对中国旅游的关注呈现3 个典型特征:①旅游关注集中在“长城、泰山、黄山、九寨沟、张家界”等少数旅游吸引物,和“北京、香港、上海、桂林”少量目的地城市;大量吸引物和目的地关注度较低,呈现“长尾现象”与极化特征.②吸引物与目的地城市的关注空间具有明显耦合性,关注度较高的吸引物多邻近或隶属于关注度较高的城市,如桂林阳朔、北京长城、成都都江堰和九寨沟、杭州西湖等.③旅游关注空间整体呈现出由高到低的“东—中—西”格局,与中国区域经济的“东—中—西”梯度格局基本耦合;北京、香港、广州、深圳、上海、成都等关注中心也与区域经济中心一致.旅游资源禀赋、电子口碑传播模式、地理区位、经济水平和关注者国家的文化背景、经济发展状况、地理区位等是影响旅游者关注度及其空间格局变化的主要因素.旅游关注度模型旨在解决互联网用户对区域旅游关注的定量计算问题,为基于互联网UGC的旅游地理学研究提供新思路.

关键词: Tripadvisor, 电子社区, 空间格局, 旅游关注度, 用户创建内容(UGC)

Abstract: Inbound tourism is an important part and indicator of tourism development in a country. International tourism is influenced by a series of factors. With the development of Internet, tourism electronic community is becoming increasingly more influential in the selection of travel destinations. User- generated content (UGC) that tourism electronic communities produce has gradually become the important source of tourism behavior and perception research. In contrast to the method of describing online attention degree only by using the number of search engine keywords, this article introduces the electronic community hierarchy as the weighting factor and establishes the model of tourist attention degree based on community UGC to adjust the focus of the model expression flexibly and optimize calculation results. Based on the web information collection technology, this study first designed an information collection process for retrieving information about Chinese tourism from an electronic community, Tripadvisor, and reconstructed this information to build a tourism information text database. The authors then built a place name database in order for using the text mining methods to obtain information about the place name frequency. The place names include two types: tourism attractions and destination cities. Based on the study of the tourist electronic community Tripadvisor, we found that attention of international users of Tripadvisor to tourism in China has three typical characteristics: (1) the focus of tourism is on the Great Wall, Mount Taishan, Mount Huangshan, Jiuzhaigou, Zhangjiajie and a small number of other tourist attractions, and a small number of destination cities such as Beijing, Hong Kong, Shanghai, and Guilin; attention degree for a large number of attractions and destination cities is low, with a long tail distribution and polarization. (2) Attention for the attractions and destination cities clearly match spatially. The attractions with high attention degree are near to or affiliated with the cities with high attention degree, such as Yangshuo in Guilin, the Great Wall in Beijing, Dujiangyan and Jiuzhaigou in Chengdu, and the West Lake in Hangzhou. (3) Tourism attention decreases from east to central and west and this pattern is consistent with the level of regional economic development in China; popular destination areas such as Beijing, Hong Kong, Guangzhou, Shenzhen, Shanghai, and Chengdu are also regional centers of economic activities. Tourism resources endowment, dissemination pattern of electronic word-of-mouth, geographic location, and level of economic development and the location, economic situation, and culture of the followers' country are the main factors influencing tourists' attention degree and its spatial pattern. This study designed a new data collection process to realize the effective management of a toponym database and tourism text database and set up a e-community tourism attention degree model that aims to solve the problem of quantitative calculation of Internet users' attention to the regional tourism and to provide a new thought for tourism geography study based on UGC from the Internet. In the visualization study, the authors analyzed the spatial distribution characteristics of attention and temporal variations. This method provides a new way for inbound tourism research.

Key words: electronic community, spatial pattern, tourism attention-degree, Tripadvisor, user-generated content (UGC)

中图分类号: 

  • P28