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An evaluation tool for backbone extraction techniques in weighted complex networks

Networks are essential for analyzing complex systems. However, their growing size necessitates backbone extraction techniques aimed at reducing their size while retaining critical features. In practice, selecting, implementing, and evaluating the most suitable backbone extraction method may be chall...

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Autores principales: Yassin, Ali, Haidar, Abbas, Cherifi, Hocine, Seba, Hamida, Togni, Olivier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10562457/
https://www.ncbi.nlm.nih.gov/pubmed/37813946
http://dx.doi.org/10.1038/s41598-023-42076-3
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author Yassin, Ali
Haidar, Abbas
Cherifi, Hocine
Seba, Hamida
Togni, Olivier
author_facet Yassin, Ali
Haidar, Abbas
Cherifi, Hocine
Seba, Hamida
Togni, Olivier
author_sort Yassin, Ali
collection PubMed
description Networks are essential for analyzing complex systems. However, their growing size necessitates backbone extraction techniques aimed at reducing their size while retaining critical features. In practice, selecting, implementing, and evaluating the most suitable backbone extraction method may be challenging. This paper introduces netbone, a Python package designed for assessing the performance of backbone extraction techniques in weighted networks. Its comparison framework is the standout feature of netbone. Indeed, the tool incorporates state-of-the-art backbone extraction techniques. Furthermore, it provides a comprehensive suite of evaluation metrics allowing users to evaluate different backbones techniques. We illustrate the flexibility and effectiveness of netbone through the US air transportation network analysis. We compare the performance of different backbone extraction techniques using the evaluation metrics. We also show how users can integrate a new backbone extraction method into the comparison framework. netbone is publicly available as an open-source tool, ensuring its accessibility to researchers and practitioners. Promoting standardized evaluation practices contributes to the advancement of backbone extraction techniques and fosters reproducibility and comparability in research efforts. We anticipate that netbone will serve as a valuable resource for researchers and practitioners enabling them to make informed decisions when selecting backbone extraction techniques to gain insights into the structural and functional properties of complex systems.
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spelling pubmed-105624572023-10-11 An evaluation tool for backbone extraction techniques in weighted complex networks Yassin, Ali Haidar, Abbas Cherifi, Hocine Seba, Hamida Togni, Olivier Sci Rep Article Networks are essential for analyzing complex systems. However, their growing size necessitates backbone extraction techniques aimed at reducing their size while retaining critical features. In practice, selecting, implementing, and evaluating the most suitable backbone extraction method may be challenging. This paper introduces netbone, a Python package designed for assessing the performance of backbone extraction techniques in weighted networks. Its comparison framework is the standout feature of netbone. Indeed, the tool incorporates state-of-the-art backbone extraction techniques. Furthermore, it provides a comprehensive suite of evaluation metrics allowing users to evaluate different backbones techniques. We illustrate the flexibility and effectiveness of netbone through the US air transportation network analysis. We compare the performance of different backbone extraction techniques using the evaluation metrics. We also show how users can integrate a new backbone extraction method into the comparison framework. netbone is publicly available as an open-source tool, ensuring its accessibility to researchers and practitioners. Promoting standardized evaluation practices contributes to the advancement of backbone extraction techniques and fosters reproducibility and comparability in research efforts. We anticipate that netbone will serve as a valuable resource for researchers and practitioners enabling them to make informed decisions when selecting backbone extraction techniques to gain insights into the structural and functional properties of complex systems. Nature Publishing Group UK 2023-10-09 /pmc/articles/PMC10562457/ /pubmed/37813946 http://dx.doi.org/10.1038/s41598-023-42076-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 Article
Yassin, Ali
Haidar, Abbas
Cherifi, Hocine
Seba, Hamida
Togni, Olivier
An evaluation tool for backbone extraction techniques in weighted complex networks
title An evaluation tool for backbone extraction techniques in weighted complex networks
title_full An evaluation tool for backbone extraction techniques in weighted complex networks
title_fullStr An evaluation tool for backbone extraction techniques in weighted complex networks
title_full_unstemmed An evaluation tool for backbone extraction techniques in weighted complex networks
title_short An evaluation tool for backbone extraction techniques in weighted complex networks
title_sort evaluation tool for backbone extraction techniques in weighted complex networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10562457/
https://www.ncbi.nlm.nih.gov/pubmed/37813946
http://dx.doi.org/10.1038/s41598-023-42076-3
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