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Adaption of the temporal correlation coefficient calculation for temporal networks (applied to a real-world pig trade network)

The average topological overlap of two graphs of two consecutive time steps measures the amount of changes in the edge configuration between the two snapshots. This value has to be zero if the edge configuration changes completely and one if the two consecutive graphs are identical. Current methods...

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Detalles Bibliográficos
Autores principales: Büttner, Kathrin, Salau, Jennifer, Krieter, Joachim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4766151/
https://www.ncbi.nlm.nih.gov/pubmed/27026862
http://dx.doi.org/10.1186/s40064-016-1811-7
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author Büttner, Kathrin
Salau, Jennifer
Krieter, Joachim
author_facet Büttner, Kathrin
Salau, Jennifer
Krieter, Joachim
author_sort Büttner, Kathrin
collection PubMed
description The average topological overlap of two graphs of two consecutive time steps measures the amount of changes in the edge configuration between the two snapshots. This value has to be zero if the edge configuration changes completely and one if the two consecutive graphs are identical. Current methods depend on the number of nodes in the network or on the maximal number of connected nodes in the consecutive time steps. In the first case, this methodology breaks down if there are nodes with no edges. In the second case, it fails if the maximal number of active nodes is larger than the maximal number of connected nodes. In the following, an adaption of the calculation of the temporal correlation coefficient and of the topological overlap of the graph between two consecutive time steps is presented, which shows the expected behaviour mentioned above. The newly proposed adaption uses the maximal number of active nodes, i.e. the number of nodes with at least one edge, for the calculation of the topological overlap. The three methods were compared with the help of vivid example networks to reveal the differences between the proposed notations. Furthermore, these three calculation methods were applied to a real-world network of animal movements in order to detect influences of the network structure on the outcome of the different methods.
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spelling pubmed-47661512016-03-29 Adaption of the temporal correlation coefficient calculation for temporal networks (applied to a real-world pig trade network) Büttner, Kathrin Salau, Jennifer Krieter, Joachim Springerplus Methodology The average topological overlap of two graphs of two consecutive time steps measures the amount of changes in the edge configuration between the two snapshots. This value has to be zero if the edge configuration changes completely and one if the two consecutive graphs are identical. Current methods depend on the number of nodes in the network or on the maximal number of connected nodes in the consecutive time steps. In the first case, this methodology breaks down if there are nodes with no edges. In the second case, it fails if the maximal number of active nodes is larger than the maximal number of connected nodes. In the following, an adaption of the calculation of the temporal correlation coefficient and of the topological overlap of the graph between two consecutive time steps is presented, which shows the expected behaviour mentioned above. The newly proposed adaption uses the maximal number of active nodes, i.e. the number of nodes with at least one edge, for the calculation of the topological overlap. The three methods were compared with the help of vivid example networks to reveal the differences between the proposed notations. Furthermore, these three calculation methods were applied to a real-world network of animal movements in order to detect influences of the network structure on the outcome of the different methods. Springer International Publishing 2016-02-24 /pmc/articles/PMC4766151/ /pubmed/27026862 http://dx.doi.org/10.1186/s40064-016-1811-7 Text en © Büttner et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Methodology
Büttner, Kathrin
Salau, Jennifer
Krieter, Joachim
Adaption of the temporal correlation coefficient calculation for temporal networks (applied to a real-world pig trade network)
title Adaption of the temporal correlation coefficient calculation for temporal networks (applied to a real-world pig trade network)
title_full Adaption of the temporal correlation coefficient calculation for temporal networks (applied to a real-world pig trade network)
title_fullStr Adaption of the temporal correlation coefficient calculation for temporal networks (applied to a real-world pig trade network)
title_full_unstemmed Adaption of the temporal correlation coefficient calculation for temporal networks (applied to a real-world pig trade network)
title_short Adaption of the temporal correlation coefficient calculation for temporal networks (applied to a real-world pig trade network)
title_sort adaption of the temporal correlation coefficient calculation for temporal networks (applied to a real-world pig trade network)
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4766151/
https://www.ncbi.nlm.nih.gov/pubmed/27026862
http://dx.doi.org/10.1186/s40064-016-1811-7
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