Big data analysis on the spatial networks of urban agglomeration

Urban agglomerations are considered as significant space typologies in the post globalization & digitalization era. The spatial linkage intensity of cities in urban agglomeration is an important basis for evaluating the development and compactness of urban agglomerations. The requirements associated with the major national strategy to achieve the coordinated development of the Beijing-Tianjin-Hebei (BTH) region and the research methods made possible by Big Data in the Internet era have created the realistic possibility of revealing the strength of spatial networks and the spatial differentiation rules of urban agglomerations. This study uses Web Crawler to obtain 500,000 sets of Weibo data in 13 cities of the BTH urban agglomeration. Three criteria and nine indicators are used to construct an index system and a model to quantitatively evaluate the strength of spatial networks in the BTH urban agglomeration. The results show that spatial network connections between cities in the urban agglomeration are not strong overall, reflecting the limited development of urban agglomeration; the spatial networks in the urban agglomeration have hierarchical and centralized characteristics, which reflect the imbalanced development of the city network; Beijing, Tianjin, and Shijiazhuang are the centers of the social network connections in the BTH urban agglomeration, which means that Weibo's online space reinforces the existing urban system; there is a positive correlation between network spatial connectivity and the hierarchy of cities in the urban agglomeration, where cities with higher levels would have more urban network connections; Generally, Weibo network connections are stronger than economic or transport links between the cities, and the development of information technology may reduce the disparity of regional development. This research innovatively uses social network big data to reveal the strength of spatial network connections and spatial differentiation rules in the urban agglomeration. The methodology provided in this paper is systematic enough for generalization.