ArticleScientific reports2017
Dynamics on networks: competition of temporal and topological correlations.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Aging effects in Schelling segregation model.Scientific reports · 2022Article
- Percolation on feature-enriched interconnected systems.Nature communications · 2021Article
- Quantifying Information without Entropy: Identifying Intermittent Disturbances in Dynamical Systems.Entropy (Basel, Switzerland) · 2020Article
- Burst-tree decomposition of time series reveals the structure of temporal correlations.Scientific reports · 2020Article
- Transmission on empirical dynamic contact networks is influenced by data processing decisions.Epidemics · 2019Article
- Correlated bursts in temporal networks slow down spreading.Scientific reports · 2018Article
- Epidemic spreading in modular time-varying networks.Scientific reports · 2018Article
- Joint effect of ageing and multilayer structure prevents ordering in the voter model.Scientific reports · 2017Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Links in many real-world networks activate and deactivate in correspondence to the sporadic interactions between the elements of the system. The activation patterns may be irregular or bursty and play an important role on the dynamics of processes taking place in the network. Information or disease spreading in networks are paradigmatic examples of this situation. Besides burstiness, several correlations may appear in the process of link activation: memory effects imply temporal correlations, but also the existence of communities in the network may mediate the activation patterns of internal an external links. Here we study the competition of topological and temporal correlations in link activation and how they affect the dynamics of systems running on the network. Interestingly, both types of correlations by separate have opposite effects: one (topological) delays the dynamics of processes on the network, while the other (temporal) accelerates it. When they occur together, our results show that the direction and intensity of the final outcome depends on the competition in a non trivial way.
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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.