中国物理B ›› 2024, Vol. 33 ›› Issue (12): 128702-128702.doi: 10.1088/1674-1056/ad84c4

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A Weibo local network growth model constructed from the perspective of following-followed

Fu-Zhong Nian(年福忠)† and Ran-Qing Yao(姚然庆)   

  1. School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, China
  • 收稿日期:2024-07-09 修回日期:2024-09-05 接受日期:2024-10-09 出版日期:2024-12-15 发布日期:2024-11-29
  • 通讯作者: Fu-Zhong Nian E-mail:gdnfz@lut.edu.cn
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant Nos. 62266030 and 61863025).

A Weibo local network growth model constructed from the perspective of following-followed

Fu-Zhong Nian(年福忠)† and Ran-Qing Yao(姚然庆)   

  1. School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730050, China
  • Received:2024-07-09 Revised:2024-09-05 Accepted:2024-10-09 Online:2024-12-15 Published:2024-11-29
  • Contact: Fu-Zhong Nian E-mail:gdnfz@lut.edu.cn
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant Nos. 62266030 and 61863025).

摘要: In order to explore the evolution process of the Weibo local network, this study first defines four factors influencing the evolution of the Weibo network. On this basis, the BA scale-free network model was enhanced by incorporating these four factors and accounting for directionality, resulting in a Weibo local network evolution model based on user attributes and behavioral similarity. The model's validity was validated by comparing simulation results with real data. The findings indicate that the Weibo local network exhibits both small-world characteristics and distinctive features. The results show that the Weibo local network exhibits both small-world characteristics and distinctive properties. The in-degree distribution follows a mixed pattern of exponential and power-law distributions, the degree-degree shows isomatching, and both the in-degree centrality and eigenvector centrality values are relatively low. This research contributes to our understanding of user behaviour in the Weibo network, and provides a structural basis for exploring the impact of Weibo network structure on information dissemination.

关键词: Weibo network, user similarity, attribute characteristics, network evolution, topology analysis

Abstract: In order to explore the evolution process of the Weibo local network, this study first defines four factors influencing the evolution of the Weibo network. On this basis, the BA scale-free network model was enhanced by incorporating these four factors and accounting for directionality, resulting in a Weibo local network evolution model based on user attributes and behavioral similarity. The model's validity was validated by comparing simulation results with real data. The findings indicate that the Weibo local network exhibits both small-world characteristics and distinctive features. The results show that the Weibo local network exhibits both small-world characteristics and distinctive properties. The in-degree distribution follows a mixed pattern of exponential and power-law distributions, the degree-degree shows isomatching, and both the in-degree centrality and eigenvector centrality values are relatively low. This research contributes to our understanding of user behaviour in the Weibo network, and provides a structural basis for exploring the impact of Weibo network structure on information dissemination.

Key words: Weibo network, user similarity, attribute characteristics, network evolution, topology analysis

中图分类号:  (Dynamics of social systems)

  • 87.23.Ge
87.23.Kg (Dynamics of evolution) 05.90.+m (Other topics in statistical physics, thermodynamics, and nonlinear dynamical systems) 89.75.-k (Complex systems)