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Mapping change in higher-order networks with multilevel and overlapping communities
Umeå University, Faculty of Science and Technology, Department of Physics.ORCID iD: 0000-0001-5859-4073
Umeå University, Faculty of Science and Technology, Department of Physics.ORCID iD: 0000-0001-5420-0591
Umeå University, Faculty of Science and Technology, Department of Physics.ORCID iD: 0000-0002-7181-9940
(English)Manuscript (preprint) (Other academic)
Abstract [en]

New network models of complex systems use layers, state nodes, or hyperedges to capture higher-order interactions and dynamics. Simplifying how the higher-order networks change over time or depending on the network model would be easy with alluvial diagrams, which visualize community splits and merges between networks. However, alluvial diagrams were developed for networks with regular nodes assigned to non-overlapping flat communities. How should they be defined for nodes in layers, state nodes, or hyperedges? How can they depict multilevel, overlapping communities? Here we generalize alluvial diagrams to map change in higher-order networks and provide an interactive tool for anyone to generate alluvial diagrams. We use the alluvial generator to illustrate the effect of modeling network flows with memory in a citation network, distinguishing multidisciplinary from field-specific journals. 

Keywords [en]
networks, community detection, the map equation
National Category
Other Physics Topics
Identifiers
URN: urn:nbn:se:umu:diva-206626DOI: 10.48550/arXiv.2303.00622OAI: oai:DiVA.org:umu-206626DiVA, id: diva2:1750384
Available from: 2023-04-13 Created: 2023-04-13 Last updated: 2023-04-13
In thesis
1. Mapping higher-order dynamics and interactions in complex networks
Open this publication in new window or tab >>Mapping higher-order dynamics and interactions in complex networks
2023 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Kartläggning av högre ordningens dynamik och interaktioner i komplexa nätverk
Abstract [en]

Complex systems research seeks to explain emergent properties in social, technological, and biological systems that result from interactions between their components. As data on the intricate relationships within these systems become increasingly available, there is a growing need for more sophisticated models to describe them accurately and offer deeper insights.

This thesis addresses challenges in incorporating higher-order interactions and dynamics into the analysis of complex systems that go beyond standard network approaches. It covers mapping changing network organizations, modeling higher-order dynamics on ordinary networks, integrating network structure and metadata, and modeling multibody interactions. The thesis offers new tools and models to enhance our understanding of how higher-order dynamics and interactions shape the organization and give rise to the function of complex systems by providing more accurate representations than traditional network models. These findings pave the way for new research in network science.

Abstract [sv]

Forskning om komplexa system strävar efter att förklara egenskaper som uppstår i sociala, teknologiska och biologiska system genom samspel mellan deras delar. När allt mer data om dessa relationer blir tillgänglig ökar behovet av mer avancerade modeller för att beskriva systemen korrekt och ge djupare insikter.

Den här avhandlingen tar upp utmaningar med att inkludera högre ordningens interaktioner och dynamik i analysen av komplexa system, genom att använda högre ordningens nätverksmodeller. Den behandlar kartläggning av förändrade nätverksstrukturer, modellering av högre ordningens dynamik i vanliga nätverk, kombinering av nätverksstruktur och metadata samt modellering av flerkroppsinteraktioner. De nya verktygen och modellerna ökar vår förståelse för hur högre ordningens dynamik och interaktioner påverkar organisationen och funktionen hos komplexa system. Detta görs genom att erbjuda mer precisa representationer än traditionella nätverksmodeller. Dessa resultat öppnar upp för framtida forskning inom nätverksvetenskap.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2023. p. 65
Keywords
networks, community detection, information theory, the map equation
National Category
Other Physics Topics
Identifiers
urn:nbn:se:umu:diva-206628 (URN)978-91-7855-984-8 (ISBN)978-91-7855-985-5 (ISBN)
Public defence
2023-05-12, NAT.D.410, Naturvetarhuset, Umeå, 09:00 (English)
Opponent
Supervisors
Available from: 2023-04-21 Created: 2023-04-13 Last updated: 2023-04-14Bibliographically approved

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Holmgren, AntonEdler, DanielRosvall, Martin

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