ArticleScientific reports2022
Looking beyond community structure leads to the discovery of dynamical communities in weighted networks.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed.
- Article
- Research on symptoms composition, time series evolution, and network visualisation of interstitial cystitis based on complex network community discovery algorithm.IET systems biology · 2024Article
- Fibration symmetries and cluster synchronization in the Caenorhabditis elegans connectome.PloS one · 2024Article
- Supermodal Decomposition of the Linear Swing Equation for Multilayer Networks.IEEE access : practical innovations, open solutions · 2022Article
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Authors and funding
4 authors.
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Abstract
A fundamental question is whether groups of nodes of a complex network can possibly display long-term cluster-synchronized behavior. While this question has been addressed for the restricted classes of unweighted and labeled graphs, it remains an open problem for the more general class of weighted networks. The emergence of coordinated motion of nodes in natural and technological networks is directly related to the network structure through the concept of an equitable partition, which determines which nodes can show long-term synchronized behavior and which nodes cannot. We provide a method to detect the presence of nearly equitable partitions in weighted networks, based on minimal information about the network structure. With this approach we are able to discover the presence of dynamical communities in both synthetic and real technological, biological, and social networks, to a statistically significant level. We show that our approach based on dynamical communities is better at predicting the emergence of synchronized behavior than existing methods to detect community structure.
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