Evidence map›Paper›PMID 29046619›Full record

ArticleMultiscale modeling & simulation : a SIAM interdisciplinary journal2017

EIGENVECTOR-BASED CENTRALITY MEASURES FOR TEMPORAL NETWORKS

Dane Taylor, Sean A Myers, Aaron Clauset, Mason A Porter, Peter J Mucha

Abstract read
In one paragraph

Article in Multiscale modeling & simulation : a SIAM interdisciplinary journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Node-layer duality in networked systems.Nature communications · 2024
    Article
  6. Eigenvector centrality for multilayer networks with dependent node importance.Complex networks & their applications. International Conference on Complex Networks and Their Applications · 2024
    Article
  7. Article
  8. Article
  9. Exploring Risk Factors in Suicidal Ideation and Attempt Concept Cooccurrence Networks.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2022
    Article
  10. Emergence of hierarchy in networked endorsement dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  11. Article
  12. Article
  13. Article
  14. A tensor-based framework for studying eigenvector multicentrality in multilayer networks.Proceedings of the National Academy of Sciences of the United States of America · 2019
    Article
  15. Article
  16. Effect of Inter-layer Coupling on Multilayer Network Centrality Measures.Journal of the Indian Institute of Science · 2019
    Article
  17. Article
  18. Article
  19. Global spectral clustering in dynamic networks.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Dane TaylorCarolina Center for Interdisciplinary Applied Mathematics, Department of Mathematics, University of North Carolina, Chapel Hill, NC 27599-3250, USA; and Statistical and Applied Mathematical Sciences Institute (SAMSI), Research Triangle Park, NC, 27709, USA.
Sean A MyersCarolina Center for Interdisciplinary Applied Mathematics, Department of Mathematics, University of North Carolina, Chapel Hill, NC 27599-3250, USA (Current address: Department of Economics, Stanford University, Stanford, CA 94305-6072, USA).
Aaron ClausetDepartment of Computer Science, University of Colorado, Boulder, CO 80309, USA; Santa Fe Institute, Santa Fe, NM 87501, USA; and BioFrontiers Institute, University of Colorado, Boulder, CO 80303, USA.
Mason A PorterMathematical Institute, University of Oxford, OX2 6GG, UK; CABDyN Complexity Centre, University of Oxford, Oxford OX1 1HP, UK; and Department of Mathematics, University of California, Los Angeles, CA 90095, USA.
Peter J MuchaCarolina Center for Interdisciplinary Applied Mathematics, Department of Mathematics, University of North Carolina, Chapel Hill, NC 27599-3250, USA.

Funding

Models and Tools for Dynamic Health-Relevant Diffusion over Complex NetworksR01HD075712 · NICHD · DUKE UNIVERSITY · PI MOODY, JAMES, MUCHA, PETER JOHN · 2013 to 2018
$1.8M
NICHD NIH HHS R01 HD075712
6 · The paper itself

Abstract

Numerous centrality measures have been developed to quantify the importances of nodes in time-independent networks, and many of them can be expressed as the leading eigenvector of some matrix. With the increasing availability of network data that changes in time, it is important to extend such eigenvector-based centrality measures to time-dependent networks. In this paper, we introduce a principled generalization of network centrality measures that is valid for any eigenvector-based centrality. We consider a temporal network with

Indexed as

05C8105C8215A1891D3094C15Eigenvector centralityHubs and authoritiesMultilayer networksRanking systemsSingular perturbationTemporal networks

Identifiers

PMID29046619
PMCPMC5643020

What OpenQuestion holds

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Registered trials

None linked

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.