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Characterizing scientific production and consumption in Physics

We analyze the entire publication database of the American Physical Society generating longitudinal (50 years) citation networks geolocalized at the level of single urban areas. We define the knowledge diffusion proxy, and scientific production ranking algorithms to capture the spatio-temporal dynam...

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Detalles Bibliográficos
Autores principales: Zhang, Qian, Perra, Nicola, Gonçalves, Bruno, Ciulla, Fabio, Vespignani, Alessandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3622083/
https://www.ncbi.nlm.nih.gov/pubmed/23571320
http://dx.doi.org/10.1038/srep01640
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author Zhang, Qian
Perra, Nicola
Gonçalves, Bruno
Ciulla, Fabio
Vespignani, Alessandro
author_facet Zhang, Qian
Perra, Nicola
Gonçalves, Bruno
Ciulla, Fabio
Vespignani, Alessandro
author_sort Zhang, Qian
collection PubMed
description We analyze the entire publication database of the American Physical Society generating longitudinal (50 years) citation networks geolocalized at the level of single urban areas. We define the knowledge diffusion proxy, and scientific production ranking algorithms to capture the spatio-temporal dynamics of Physics knowledge worldwide. By using the knowledge diffusion proxy we identify the key cities in the production and consumption of knowledge in Physics as a function of time. The results from the scientific production ranking algorithm allow us to characterize the top cities for scholarly research in Physics. Although we focus on a single dataset concerning a specific field, the methodology presented here opens the path to comparative studies of the dynamics of knowledge across disciplines and research areas.
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spelling pubmed-36220832013-04-10 Characterizing scientific production and consumption in Physics Zhang, Qian Perra, Nicola Gonçalves, Bruno Ciulla, Fabio Vespignani, Alessandro Sci Rep Article We analyze the entire publication database of the American Physical Society generating longitudinal (50 years) citation networks geolocalized at the level of single urban areas. We define the knowledge diffusion proxy, and scientific production ranking algorithms to capture the spatio-temporal dynamics of Physics knowledge worldwide. By using the knowledge diffusion proxy we identify the key cities in the production and consumption of knowledge in Physics as a function of time. The results from the scientific production ranking algorithm allow us to characterize the top cities for scholarly research in Physics. Although we focus on a single dataset concerning a specific field, the methodology presented here opens the path to comparative studies of the dynamics of knowledge across disciplines and research areas. Nature Publishing Group 2013-04-10 /pmc/articles/PMC3622083/ /pubmed/23571320 http://dx.doi.org/10.1038/srep01640 Text en Copyright © 2013, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by-nc-sa/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-ShareALike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/
spellingShingle Article
Zhang, Qian
Perra, Nicola
Gonçalves, Bruno
Ciulla, Fabio
Vespignani, Alessandro
Characterizing scientific production and consumption in Physics
title Characterizing scientific production and consumption in Physics
title_full Characterizing scientific production and consumption in Physics
title_fullStr Characterizing scientific production and consumption in Physics
title_full_unstemmed Characterizing scientific production and consumption in Physics
title_short Characterizing scientific production and consumption in Physics
title_sort characterizing scientific production and consumption in physics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3622083/
https://www.ncbi.nlm.nih.gov/pubmed/23571320
http://dx.doi.org/10.1038/srep01640
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