Evidence map›Paper›PMID 35854964›Full record

ReviewApplied network science2022

Exploring the

D Morrison, M Bedinger, L Beevers, K McClymont

Abstract readReview
In one paragraph

Review in Applied network science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

4 authors.

D MorrisonSchool of Energy, Geosciences, Infrastructure and Society, Heriot-Watt University, William Arrol Building, Room W.A. 3.36/3.37, 2 Third Gait, Currie, Edinburgh, EH14 4AS UK.ORCID 0000-0003-4612-081X
M BedingerSchool of Energy, Geosciences, Infrastructure and Society, Heriot-Watt University, William Arrol Building, Room W.A. 3.36/3.37, 2 Third Gait, Currie, Edinburgh, EH14 4AS UK.ORCID 0000-0001-6097-1595
L BeeversSchool of Energy, Geosciences, Infrastructure and Society, Heriot-Watt University, William Arrol Building, Room W.A. 3.36/3.37, 2 Third Gait, Currie, Edinburgh, EH14 4AS UK.ORCID 0000-0002-1597-273X
K McClymontSchool of Energy, Geosciences, Infrastructure and Society, Heriot-Watt University, William Arrol Building, Room W.A. 3.36/3.37, 2 Third Gait, Currie, Edinburgh, EH14 4AS UK.ORCID 0000-0003-0235-7786

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Network analysis is a useful tool to analyse the interactions and structure of graphs that represent the relationships among entities, such as sectors within an urban system. Connecting entities in this way is vital in understanding the complexity of the modern world, and how to navigate these complexities during an event. However, the field of network analysis has grown rapidly since the 1970s to produce a vast array of available metrics that describe different graph properties. This diversity allows network analysis to be applied across myriad research domains and contexts, however widespread applications have produced polysemic metrics. Challenges arise in identifying which method of network analysis to adopt, which metrics to choose, and how many are suitable. This paper undertakes a structured review of literature to provide clarity on Supplementary Information: The online version contains supplementary material available at 10.1007/s41109-022-00476-w.

Indexed as

Disaster managementGraph theoryNatural hazardsNetwork analysisUrban systems

Identifiers

PMID35854964
PMCPMC9281375

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.