Analysis of Research Topics and Scientific Collaborations in Renewable Energy Using Community Detection
Renewable energy is a key breakthrough to mitigate carbon emissions, to reduce global warming, and for the creation of sustainable societies. Renewable energy is a broad area that includes different technologies that are being continuously improved to increase their efficiency and reduce cost. Many...
| Main Authors: | , , , , |
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| Format: | info:eu-repo/semantics/article |
| Language: | English |
| Published: |
MDPI
2020
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10835/7640 |
| _version_ | 1789406412456067072 |
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| author | Alcayde García, Alfredo Gil Montoya, Francisco Baños Navarro, Raúl Perea Moreno, Alberto Jesús Manzano Agugliaro, Francisco |
| author_facet | Alcayde García, Alfredo Gil Montoya, Francisco Baños Navarro, Raúl Perea Moreno, Alberto Jesús Manzano Agugliaro, Francisco |
| author_sort | Alcayde García, Alfredo |
| collection | DSpace |
| description | Renewable energy is a key breakthrough to mitigate carbon emissions, to reduce global warming, and for the creation of sustainable societies. Renewable energy is a broad area that includes different technologies that are being continuously improved to increase their efficiency and reduce cost. Many papers have been published in the last decades dealing with renewable energy issues, which is why it becomes important to determine the main topics of research, the main publications devoted to publishing scientific papers about renewable energy, and how researchers collaborate in this discipline. With these aims in view, this paper presents an advanced method for analysing publications about renewable energy and scientific collaboration networks in this field. This method is based on automatically obtaining bibliographic data from scientific publications through the use of the Scopus Database API Interface, which are then analysed using community detection algorithms and graph visualization software. The results obtained show that it is possible to determine the main areas of research activity as well as to identify the structures of the collaboration network in the field of renewable energy. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-7640 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2020 |
| publisher | MDPI |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-76402023-04-12T19:29:56Z Analysis of Research Topics and Scientific Collaborations in Renewable Energy Using Community Detection Alcayde García, Alfredo Gil Montoya, Francisco Baños Navarro, Raúl Perea Moreno, Alberto Jesús Manzano Agugliaro, Francisco renewable energy sustainability research activity scientific collaborations complex networks community detection Renewable energy is a key breakthrough to mitigate carbon emissions, to reduce global warming, and for the creation of sustainable societies. Renewable energy is a broad area that includes different technologies that are being continuously improved to increase their efficiency and reduce cost. Many papers have been published in the last decades dealing with renewable energy issues, which is why it becomes important to determine the main topics of research, the main publications devoted to publishing scientific papers about renewable energy, and how researchers collaborate in this discipline. With these aims in view, this paper presents an advanced method for analysing publications about renewable energy and scientific collaboration networks in this field. This method is based on automatically obtaining bibliographic data from scientific publications through the use of the Scopus Database API Interface, which are then analysed using community detection algorithms and graph visualization software. The results obtained show that it is possible to determine the main areas of research activity as well as to identify the structures of the collaboration network in the field of renewable energy. 2020-01-20T09:40:24Z 2020-01-20T09:40:24Z 2018-11-30 info:eu-repo/semantics/article 2071-1050 http://hdl.handle.net/10835/7640 en https://www.mdpi.com/2071-1050/10/12/4510 Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess MDPI |
| spellingShingle | renewable energy sustainability research activity scientific collaborations complex networks community detection Alcayde García, Alfredo Gil Montoya, Francisco Baños Navarro, Raúl Perea Moreno, Alberto Jesús Manzano Agugliaro, Francisco Analysis of Research Topics and Scientific Collaborations in Renewable Energy Using Community Detection |
| title | Analysis of Research Topics and Scientific Collaborations in Renewable Energy Using Community Detection |
| title_full | Analysis of Research Topics and Scientific Collaborations in Renewable Energy Using Community Detection |
| title_fullStr | Analysis of Research Topics and Scientific Collaborations in Renewable Energy Using Community Detection |
| title_full_unstemmed | Analysis of Research Topics and Scientific Collaborations in Renewable Energy Using Community Detection |
| title_short | Analysis of Research Topics and Scientific Collaborations in Renewable Energy Using Community Detection |
| title_sort | analysis of research topics and scientific collaborations in renewable energy using community detection |
| topic | renewable energy sustainability research activity scientific collaborations complex networks community detection |
| url | http://hdl.handle.net/10835/7640 |
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