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Identifying Modular Flows on Multilayer Networks Reveals Highly Overlapping Organization in Interconnected Systems
Umeå University, Faculty of Science and Technology, Department of Physics.
Umeå University, Faculty of Science and Technology, Department of Physics.
2015 (English)In: Physical Review X, ISSN 2160-3308, E-ISSN 2160-3308, Vol. 5, no 1, 011027Article in journal (Refereed) Published
Abstract [en]

To comprehend interconnected systems across the social and natural sciences, researchers have developed many powerful methods to identify functional modules. For example, with interaction data aggregated into a single network layer, flow-based methods have proven useful for identifying modular dynamics in weighted and directed networks that capture constraints on flow processes. However, many interconnected systems consist of agents or components that exhibit multiple layers of interactions, possibly from several different processes. Inevitably, representing this intricate network of networks as a single aggregated network leads to information loss and may obscure the actual organization. Here, we propose a method based on a compression of network flows that can identify modular flows both within and across layers in nonaggregated multilayer networks. Our numerical experiments on synthetic multilayer networks, with some layers originating from the same interaction process, show that the analysis fails in aggregated networks or when treating the layers separately, whereas the multilayer method can accurately identify modules across layers that originate from the same interaction process. We capitalize on our findings and reveal the community structure of two multilayer collaboration networks with topics as layers: scientists affiliated with the Pierre Auger Observatory and scientists publishing works on networks on the arXiv. Compared to conventional aggregated methods, the multilayer method uncovers connected topics and reveals smaller modules with more overlap that better capture the actual organization.

Place, publisher, year, edition, pages
2015. Vol. 5, no 1, 011027
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URN: urn:nbn:se:umu:diva-102454DOI: 10.1103/PhysRevX.5.011027ISI: 000351284800001OAI: oai:DiVA.org:umu-102454DiVA: diva2:812774
Available from: 2015-05-20 Created: 2015-04-26 Last updated: 2017-12-04Bibliographically approved

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