Analysis of dynamic networks based on the Ising model for the case of study of co-authorship of scientific articles

Abstract Two computational methods based on the Ising model were implemented for studying temporal dynamic in co-authorship networks: an interpretative for real networks and another for simulation via Monte Carlo. The objective of simulation networks is to evaluate if the Ising model describes in si...

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Autores principales:	V. Andrea Hurtado-Marín, J. Dario Agudelo-Giraldo, Sebastian Robledo, Elisabeth Restrepo-Parra
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/0e3eb03576fc4775bbe0da8e1298e478
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spelling	oai:doaj.org-article:0e3eb03576fc4775bbe0da8e1298e4782021-12-02T15:53:44ZAnalysis of dynamic networks based on the Ising model for the case of study of co-authorship of scientific articles10.1038/s41598-021-85041-82045-2322https://doaj.org/article/0e3eb03576fc4775bbe0da8e1298e4782021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-85041-8https://doaj.org/toc/2045-2322Abstract Two computational methods based on the Ising model were implemented for studying temporal dynamic in co-authorship networks: an interpretative for real networks and another for simulation via Monte Carlo. The objective of simulation networks is to evaluate if the Ising model describes in similar way the dynamic of the network and of the magnetic system, so that it can be found a generalized explanation to the behaviours observed in real networks. The scientific papers used for building the real networks were acquired from WoS core collection. The variables for each record took into account bibliographic references. The search equation for each network considered specific topics trying to obtain an advanced temporal evolution in terms of the addition of new nodes; that means 3 steps, a time to reach the interest of the scientific community, a gradual increase until reaching a peak and finally, a decreasing trend by losing of novelty. It is possible to conclude that both methods are consistent with each other, showing that the Ising model can predict behaviours such as the number and size of communities (or domains) according to the temporal distribution of new nodes.V. Andrea Hurtado-MarínJ. Dario Agudelo-GiraldoSebastian RobledoElisabeth Restrepo-ParraNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q V. Andrea Hurtado-Marín J. Dario Agudelo-Giraldo Sebastian Robledo Elisabeth Restrepo-Parra Analysis of dynamic networks based on the Ising model for the case of study of co-authorship of scientific articles
description	Abstract Two computational methods based on the Ising model were implemented for studying temporal dynamic in co-authorship networks: an interpretative for real networks and another for simulation via Monte Carlo. The objective of simulation networks is to evaluate if the Ising model describes in similar way the dynamic of the network and of the magnetic system, so that it can be found a generalized explanation to the behaviours observed in real networks. The scientific papers used for building the real networks were acquired from WoS core collection. The variables for each record took into account bibliographic references. The search equation for each network considered specific topics trying to obtain an advanced temporal evolution in terms of the addition of new nodes; that means 3 steps, a time to reach the interest of the scientific community, a gradual increase until reaching a peak and finally, a decreasing trend by losing of novelty. It is possible to conclude that both methods are consistent with each other, showing that the Ising model can predict behaviours such as the number and size of communities (or domains) according to the temporal distribution of new nodes.
format	article
author	V. Andrea Hurtado-Marín J. Dario Agudelo-Giraldo Sebastian Robledo Elisabeth Restrepo-Parra
author_facet	V. Andrea Hurtado-Marín J. Dario Agudelo-Giraldo Sebastian Robledo Elisabeth Restrepo-Parra
author_sort	V. Andrea Hurtado-Marín
title	Analysis of dynamic networks based on the Ising model for the case of study of co-authorship of scientific articles
title_short	Analysis of dynamic networks based on the Ising model for the case of study of co-authorship of scientific articles
title_full	Analysis of dynamic networks based on the Ising model for the case of study of co-authorship of scientific articles
title_fullStr	Analysis of dynamic networks based on the Ising model for the case of study of co-authorship of scientific articles
title_full_unstemmed	Analysis of dynamic networks based on the Ising model for the case of study of co-authorship of scientific articles
title_sort	analysis of dynamic networks based on the ising model for the case of study of co-authorship of scientific articles
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/0e3eb03576fc4775bbe0da8e1298e478
work_keys_str_mv	AT vandreahurtadomarin analysisofdynamicnetworksbasedontheisingmodelforthecaseofstudyofcoauthorshipofscientificarticles AT jdarioagudelogiraldo analysisofdynamicnetworksbasedontheisingmodelforthecaseofstudyofcoauthorshipofscientificarticles AT sebastianrobledo analysisofdynamicnetworksbasedontheisingmodelforthecaseofstudyofcoauthorshipofscientificarticles AT elisabethrestrepoparra analysisofdynamicnetworksbasedontheisingmodelforthecaseofstudyofcoauthorshipofscientificarticles
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Analysis of dynamic networks based on the Ising model for the case of study of co-authorship of scientific articles

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