ArticleNature communications2022
From subcritical behavior to a correlation-induced transition in rumor models.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 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
- Impact of information dissemination and behavioural responses on epidemic dynamics: A multi-layer network analysis.Infectious Disease Modelling · 2025Article
- Rumor detection model with weighted GraphSAGE focusing on node location.Scientific reports · 2024Article
- Modelling and predicting online vaccination views using bow-tie decomposition.Royal Society open science · 2024Article
- Configurational patterns for COVID-19 related social media rumor refutation effectiveness enhancement based on machine learning and fsQCA.Information processing & management · 2023Article
- A game theoretical model for the stimulation of public cooperation in environmental collaborative governance.Royal Society open science · 2022Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rumors and information spreading emerge naturally from human-to-human interactions and have a growing impact on our everyday life due to increasing and faster access to information, whether trustworthy or not. A popular mathematical model for spreading rumors, data, or news is the Maki-Thompson model. Mean-field approximations suggested that this model does not have a phase transition, with rumors always reaching a fraction of the population. Conversely, here, we show that a continuous phase transition is present in this model. Moreover, we explore a modified version of the Maki-Thompson model that includes a forgetting mechanism, changing the Markov chain's nature and allowing us to use a plethora of analytic and numeric methods. Particularly, we characterize the subcritical behavior, where the lifespan of a rumor increases as the spreading rate drops, following a power-law relationship. Our findings show that the dynamic behavior of rumor models is much richer than shown in previous investigations.
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