Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Modelling sequences and temporal networks with dynamic community structures
Umeå University, Faculty of Science and Technology, Department of Physics.
2017 (English)In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 8, 582Article in journal (Refereed) Published
Abstract [en]

In evolving complex systems such as air traffic and social organisations, collective effects emerge from their many components' dynamic interactions. While the dynamic interactions can be represented by temporal networks with nodes and links that change over time, they remain highly complex. It is therefore often necessary to use methods that extract the temporal networks' large-scale dynamic community structure. However, such methods are subject to overfitting or suffer from effects of arbitrary, a priori-imposed timescales, which should instead be extracted from data. Here we simultaneously address both problems and develop a principled data-driven method that determines relevant timescales and identifies patterns of dynamics that take place on networks, as well as shape the networks themselves. We base our method on an arbitrary-order Markov chain model with community structure, and develop a nonparametric Bayesian inference framework that identifies the simplest such model that can explain temporal interaction data.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP , 2017. Vol. 8, 582
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-140461DOI: 10.1038/s41467-017-00148-9ISI: 000411166800001PubMedID: 28928409OAI: oai:DiVA.org:umu-140461DiVA: diva2:1152622
Available from: 2017-10-25 Created: 2017-10-25 Last updated: 2017-10-25Bibliographically approved

Open Access in DiVA

fulltext(3141 kB)5 downloads
File information
File name FULLTEXT01.pdfFile size 3141 kBChecksum SHA-512
a44814250e37c7a31154f5578f56867628fc7e73bece0ba69c811bcc021d56c8891c7581db754333a8a9d03f6ddc44d9984b650ce96ef6943e4e03e3b6a7513b
Type fulltextMimetype application/pdf

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Rosvall, Martin
By organisation
Department of Physics
In the same journal
Nature Communications
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 5 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 28 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf