Analysis of Urban Space Vitality Based on Weibo Check-In Data : A Case Study of Suzhou

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The city is a carrier of all kinds of residents' activities and the core of public activities. With the rapid process of urbanization in China, the spatial structure of cities has been spreading, and in some cities, urban space has been redefined due to the construction of new districts and new cities, and the urban spatial structure has gradually evolved from a single center to a multicenter. In urban planning practice, multicentricity has become one of the common planning tools in major cities in recent years, and mega cities in China such as Beijing, Shanghai, Guangzhou, and Shenzhen all take multicentricity as the goal of urban development. The research on urban spatial structure in China mainly involves: theoretical studies, studies on the characteristics of urban spatial structure patterns, studies on the relevance of urban structure to social problems, and the exploration of the relevance of urban structure to social economy. The current stage of research mainly explores the spatial structure of cities by using planning and census data as the main data source and geospatial and morphological analysis as the method. However, these data have certain limitations, one of which is that the data accuracy is not sufficient to analyze the urban residents' aggregation within urban space at all scales, and the other is that the data are not real-time and cannot reflect the mobility characteristics of urban residents. In recent years, with the development of information technology, big data has provided new data sources for urban spatial analysis. Among them, the more widely used are: social network pictures, night lighting data, shared bicycle travel data, heat map data, cell phone signaling data, and online taxi travel data, etc. Scholars such as Ying Long, Lu Yu, and Zhiying Li have used these data to analyze urban space. However, these data have problems such as difficulty of access and few access channels for scholars. And the open-source Weibo check-in data provides a reliable alternative. Weibo check-in data records the check-in information of Sina Weibo users, which mainly includes information such as check-in time, check-in content, spatial location of check-in points, and the number of check-ins at check-in points. The Weibo check-in data can be obtained through an API interface, which is easier to obtain compared with the other data which has mentioned before, and has been widely adopted in the current stage of urban spatial research. At present, domestic scholars mainly use Weibo check-in data as a measurement of foot traffic in various spaces and as a method to identify urban functional areas, but less research has been conducted on urban spatial vitality with this kind of big data.
urban space vitality, weibo, China, Suzhou, check-in data, urban spatial structure patterns, social media, social media data