ArticleProceedings of the National Academy of Sciences of the United States of America2025
Spreading dynamics of information on online social networks.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The trial behind it
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Who cites it
8 citing papers in PubMed.
- Quantifying the Dynamics of Network Detachment Across Scientific, Technological, Commercial, and Pharmacological Domains.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Morphing polymer voxels for dynamic information switching.Science advances · 2026Article
- Explainable generative 3D design driven by social media semantics.Nature communications · 2026Article
- The quality and reliability of short videos about chronic obstructive pulmonary disease on TikTok and Bilibili: a cross-sectional study.Journal of thoracic disease · 2026Article
- Characterizing Information Propagation in Social Media with Branching Processes.Entropy (Basel, Switzerland) · 2026Article
- Editorial Perspective: How spreading mental health information can be (un-) helpful - a dynamic systems approach.Journal of child psychology and psychiatry, and allied disciplines · 2026Article
- An Exploration of How Functional Neurological Disorder Is Discussed on X (Twitter): Mixed Methods Study Using Social Network and Content Analysis.Journal of medical Internet research · 2025Article
- The Online Misinformation Susceptibility Scale: Development and Initial Validation.Healthcare (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.