ArticleNature communications2026
Rumor propagation on hypergraphs.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Efficient Gillespie algorithms for spreading phenomena in large and heterogeneous higher-order networks.Nature communications · 2026Article
- Rumor propagation on hypergraphs.Nature communications · 2026Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The rapid spread of information and rumors through social media platforms, especially in group settings, motivates the need for more sophisticated models of rumor propagation. Traditional pairwise models do not account for group interactions, a limitation that we address by proposing a higher-order rumor model based on hypergraphs. Our model incorporates a group-based annihilation mechanism, where a spreader becomes a stifler when the fraction of hyperedges aware of the rumor exceeds a threshold. The dynamics has two distinct subcritical behaviors: exponential and power-law decay, which can coexist depending on the heterogeneity of the hypergraph. Interestingly, in the set of parameters we analysed, we found continuous phase transitions in both homogeneous and heterogeneous hypergraphs. This finding aligns with the literature suggesting that real-world rumor propagation occurs near criticality. Finally, we validated our model using empirical data from Telegram and email cascades, which provides additional evidence and possible explanations for this criticality claim. These results open the door to a more detailed understanding of rumor dynamics in higher-order systems.
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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.