Abstract
The spatial interaction of urban system has been an hot research issue in the field of urban research. In this paper, user’s microblog spatial information data were used to discern the spatial structure of an urban area. Firstly, Sina Weibo microblog data for 2011–2015 were used to establish a thematic database of cities along the Huaihe River Basin, China. Secondly, network connectivity, inflow, and outflow of three indicator systems were analyzed. Finally, combining this database with socioeconomic data, experimental verification and comparative analysis were carried out. The study found that the urban spatial relation in the Huaihe River Basin has the following characteristics: the spatial difference of urban size distribution is obvious; urban layout presents a stratified aggregation phenomenon; and the high-grade cities lead the city’s interaction. The research shows that this method of data mining for urban interaction in the Huaihe River Basin is valid and that this research into urban spatial patterns of river basins is applicable to other areas.
Highlights
In the four decades since China’s reform, the urban population has increased from 170 million in 1978 to 790 million in 2016 and the urbanization rate has increased from 17.9% to 57.4% [1]
Information flow can most directly reflect the degree of urban spatial interaction [7]
Does socioeconomic status affect users’ travel and activity rules? How does it affect? In order to answer these questions, this paper analyzes the correlation among urban microblog registration data, urban population, and GDP with the statistical data
Summary
In the four decades since China’s reform, the urban population has increased from 170 million in 1978 to 790 million in 2016 and the urbanization rate has increased from 17.9% to 57.4% [1]. Information flow can most directly reflect the degree of urban spatial interaction [7] Research on this aspect studied the transmission of mail. E flow and consumption of network information can reflect the level of urbanization [12], which can provide basic data for geographical and sociological studies [13, 14]. As for the typical spatial-temporal characteristics of social media data, many data mining research papers have analyzed information, such as urban hot events [22], identifying urban Corridors [23], geography of happiness [24], whereabouts of people [25], urban function connectivity [26], urban spatial interaction [27], revaluating urban space [28], and characterizing witness accounts [29]. Given that the Huaihe River Basin is a natural geographical unit and does not coincide with the boundaries of the administrative units, the study only selected the 26 cities whose governmental units are entirely in the Huaihe River Basin for calculation and analysis (Figure 1)
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