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Exploring the raison d’etre behind metric selection in network analysis: a systematic review
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 compl...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9281375/ https://www.ncbi.nlm.nih.gov/pubmed/35854964 http://dx.doi.org/10.1007/s41109-022-00476-w |
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author | Morrison, D. Bedinger, M. Beevers, L. McClymont, K. |
author_facet | Morrison, D. Bedinger, M. Beevers, L. McClymont, K. |
author_sort | Morrison, D. |
collection | PubMed |
description | 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 raison d’etre behind metric selection and suggests a way forward for applied network analysis. It is essential that future studies explicitly report the rationale behind metric choice and describe how the mathematics relates to target concepts and themes. An exploratory metric analysis is an important step in identifying the most important metrics and understanding redundant ones. Finally, where applicable, one should select an optimal number of metrics that describe the network both locally and globally, so as to understand the interactions and structure as holistically as possible. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s41109-022-00476-w. |
format | Online Article Text |
id | pubmed-9281375 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-92813752022-07-15 Exploring the raison d’etre behind metric selection in network analysis: a systematic review Morrison, D. Bedinger, M. Beevers, L. McClymont, K. Appl Netw Sci Review 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 raison d’etre behind metric selection and suggests a way forward for applied network analysis. It is essential that future studies explicitly report the rationale behind metric choice and describe how the mathematics relates to target concepts and themes. An exploratory metric analysis is an important step in identifying the most important metrics and understanding redundant ones. Finally, where applicable, one should select an optimal number of metrics that describe the network both locally and globally, so as to understand the interactions and structure as holistically as possible. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s41109-022-00476-w. Springer International Publishing 2022-07-14 2022 /pmc/articles/PMC9281375/ /pubmed/35854964 http://dx.doi.org/10.1007/s41109-022-00476-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Review Morrison, D. Bedinger, M. Beevers, L. McClymont, K. Exploring the raison d’etre behind metric selection in network analysis: a systematic review |
title | Exploring the raison d’etre behind metric selection in network analysis: a systematic review |
title_full | Exploring the raison d’etre behind metric selection in network analysis: a systematic review |
title_fullStr | Exploring the raison d’etre behind metric selection in network analysis: a systematic review |
title_full_unstemmed | Exploring the raison d’etre behind metric selection in network analysis: a systematic review |
title_short | Exploring the raison d’etre behind metric selection in network analysis: a systematic review |
title_sort | exploring the raison d’etre behind metric selection in network analysis: a systematic review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9281375/ https://www.ncbi.nlm.nih.gov/pubmed/35854964 http://dx.doi.org/10.1007/s41109-022-00476-w |
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