Acta Scientiarum Naturalium Universitatis Pekinensis ›› 2019, Vol. 55 ›› Issue (3): 473-481.DOI: 10.13209/j.0479-8023.2018.033

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Feature Analysis of City’s Tourism Districts Based on Social Media: A Case Study of Suzhou

WANG Wenfu1,2, CHEN Zihao1,2, SUN Qi1,2, ZHANG Yi1,2,†   

  1. 1. Institute of Remote Sensing and Geographical Information System, Peking University, Beijing 100871 2. Beijing Key Laboratory of Spatial Information Integration and Its Applications, Beijing 100871
  • Received:2018-04-09 Revised:2018-05-15 Online:2019-05-20 Published:2019-05-20
  • Contact: ZHANG Yi,E-mail:zy(at)pku.edu.cn

基于社交媒体的城市旅游区特征分析——以苏州市为例

王雯夫1,2, 陈子豪1,2, 孙奇1,2, 张毅1,2,†   

  1. 1. 北京大学遥感与地理信息系统研究所, 北京100871 2. 空间信息集成与3S 工程应用北京市重点实验室, 北京 100871
  • 通讯作者: 张毅,E-mail:zy(at)pku.edu.cn
  • 基金资助:
    国家重点研发计划项目(2018YFB0505000)资助

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Abstract:

A new method is proposed using area feature-tourism districts as analysis unit. Firstly, spatial-temporal behaviors of individual tourists are extracted from social media data. Secondly, the city’s tourism districts are extracted based on spatial-temporal behaviors. Finally, tourism districts are analyzed by 3 kinds of features — ourist activity features, tourist origin features and the structure features of tourism district network using tourism districts as nodes and tourist flow as edges. In the empirical research of Suzhou, 7 tourism districts are extracted based on spatial-temporal behaviors. The spatial structure of tourism districts is generally the same as “1-core-1-corridor-3-district” pattern in Suzhou tourism planning. The feature analysis of Suzhou tourism districts indicates that the Ancient City Tourism District and the Ancient Town Tourism District are the core tourism districts, which attracts tourists from various and distant origins. The tourism districts in and near Suzhou urban area attract more tourists. Suzhou tourism districts have already formed into a multi-core structure. This research shows the effectiveness of extracting city’s tourism districts based on social media data and researching city’s tourism with tourism districts as analysis unit, providing a new approach for research on urban tourism.

Key words: urban tourism, social media, special-temporal behavior, tourism district, network analysis

摘要：

提出以面状旅游区为分析单元的新方法。首先从海量社交媒体数据中提取个体旅游时空行为, 然后基于行为计算城市的旅游区结构, 最后分析旅游区的游客行为特征和游客客源特征,以旅游区为节点、旅游区之间的旅游流为关系构建旅游区网络, 并分析其结构特征。在对苏州市的实证研究中, 基于行为计算得到7个旅游区, 这一结果与苏州市旅游规划中的“一核一带三区”空间格局基本上一致。对苏州市旅游区的特征分析表明: 1) 古城和古镇是苏州市旅游的核心区域, 游客分散且距离远; 2) 苏州城区及附近的旅游区更能吸引跨旅游区的旅游行为; 3) 苏州旅游区网络已经形成多中心结构。通过实证研究, 验证了基于社交媒体数据计算城市旅游区结构和以面状旅游区为分析单元研究城市旅游的有效性, 为城市旅游研究提供新思路。

关键词: 城市旅游, 社交媒体；时空行为, 旅游区, 网络分析

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