PROGRESS IN GEOGRAPHY ›› 2023, Vol. 42 ›› Issue (7): 1272-1284.doi: 10.18306/dlkxjz.2023.07.004

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Urban network characteristics and influencing factors based on Douyin (TikTok) social media platform

WANG Yan1(), XIU Chunliang2,*()   

  1. 1. College of Humanities and Law, Northeastern University, Shenyang 110169, China
    2. Jangho Architecture College, Northeastern University, Shenyang 110169, China
  • Received:2023-01-03 Revised:2023-04-14 Online:2023-07-28 Published:2023-07-25
  • Contact: XIU Chunliang;
  • Supported by:
    National Natural Science Foundation of China(41871162)


With the development of 5G, AI, and the Internet, we have entered the era of video socialization. Based on the Douyin (TikTok) data, this study analyzed the characteristics of the urban network in China with the help of the social network analysis method, and explored the influencing factors by using the optimal parameters-based geographical detector. The results show that: 1) The unbalanced distribution pattern of different types of cities based on local and non-local connections is basically consistent with the long-standing east-west gap, and the city grade based on the Douyin (TikTok) social media platform does not completely follow the traditional city grade system. 2) The overall network showed a triangular pyramid structure, which is very similar to the development pattern of urban agglomerations in the 14th Five-Year Plan. 3) The main influencing factors of urban network centrality in China are the level of economic development and information development, and the secondary influencing factors are the level of logistics development and tourism development. 4) Due to the varied stages of development, different regions showed obvious spatial differences. The southwestern region was more affected by the level of logistics development, the northeastern region was more affected by the level of tourism development, and the northwestern region was more affected by the level of economic development.

Key words: Douyin (TikTok) data, social network analysis, optimal parameters-based geographical detector, ur-ban network in China