Spreading dynamics of information on online social networks

• 成果类型: Article
• 署名作者: Meng, Fanhui; Xie, Jiarong; Sun, Jiachen; Xu, Cong; Zeng, Yutian; Wang, Xiangrong; Jia, Tao; Huang, Shuhong; Deng, Youjin; Hu, Yanqing
• 署名单位: Sun Yat Sen University; Beijing Normal University; Beijing Normal University; Sun Yat Sen University; Southern University of Science & Technology; Shenzhen University; Chongqing Normal University; Southwest University - China; Technical University of Munich; Chinese Academy of Sciences; University of Science & Technology of China, CAS; Minjiang University; Southern University of Science & Technology
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-13613
• DOI: 10.1073/pnas.2410227122
• 发表日期: 2025-01-28
• 关键词: news

摘要

Social media is profoundly changing our society with its unprecedented spreading power. Due to the complexity of human behaviors and the diversity of massive messages, the information-spreading dynamics are complicated, and the reported mechanisms are different and even controversial. Based on data from mainstream social media platforms, including WeChat, Weibo, and Twitter, cumulatively encompassing a total of 7.45 billion users, we uncover a ubiquitous mechanism that the information- spreading dynamics are basically driven by the interplay of social reinforcement and social weakening effects. Accordingly, we propose a concise equation, which, surprisingly, can well describe all the empirical large-scale spreading trajectories. Our theory resolves a number of controversial claims and satisfactorily explains many phenomena previously observed. It also reveals that the highly clustered nature of social networks can lead to rapid and high-frequency information bursts with relatively small coverage per burst. This vital feature enables social media to have a high capacity and diversity for information dissemination, beneficial for its ecological development.