Research on the relationship between residents' fitness and urban space based on social media data: a case study of Changsha Zhuzhou Xiangtan area
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Yu CHEN, Shaoyao He, Jianmin Zhao, Yuanqiang Tang
Under the background of big data, social media data, as an important spatial data, plays a very important role in the research of urban residents' spatiotemporal behavior. In this paper, through crawling the data of sina Weibo with text and location information in Changsha Zhuzhou Xiangtan area, this paper selects more than 10000 pieces of data related to urban residents' fitness behavior by manual tagging and machine learning. After data cleaning, LDA method is used to analyze the text and extract the subordinate topics related to fitness behavior Nuclear density analysis and fishing net analysis reveal the spatial characteristics of healthy sports and the social, economic, cultural and other factors that affect their distribution. It is of great significance for government departments and planning departments to examine and analyze the spatial structure of healthy cities in rapid development and guide the spatial planning and construction of healthy sports and industrial selection.
Social media data, LDA, social behavior, nuclear density analysis