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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2013
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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. |
format | Online Article Text |
id | pubmed-3622083 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
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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