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Bibliometric Tools for Discovering Information in Database
dc.contributor.author | Herrera-Viedma, Enrique | |
dc.contributor.author | Martínez, M. Angeles | |
dc.contributor.author | Herrera Gómez, Manuel | |
dc.date | 2016 | |
dc.date.accessioned | 2020-04-13T07:02:31Z | |
dc.date.available | 2020-04-13T07:02:31Z | |
dc.identifier.isbn | 9783319420073 | |
dc.identifier.issn | 0302-9743 | |
dc.identifier.uri | https://reunir.unir.net/handle/123456789/9949 | |
dc.description.abstract | In bibliometrics, there are two main procedures to explore a research field: performance analysis and science mapping. Performance analysis aims at evaluating groups of scientific actors (countries, universities, departments, researchers) and the impact of their activity on the basis of bibliographic data. Science mapping aims at displaying the structural and dynamic aspects of scientific research, delimiting a research field, and quantifying and visualizing the detected sub-fields by means of co-word analysis or documents co-citation analysis. In this paper we present two bibliometric tools that we have developed in our research laboratory SECABA: (i) H-Classics to develop performance analysis based on Highly Cited Papers and (ii) SciMAT to develop science mapping guided by performance bibliometric indicators. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Trends in applied knowledge-based systems and data science | es_ES |
dc.relation.ispartofseries | ;vol. 9799 | |
dc.relation.uri | https://link.springer.com/chapter/10.1007/978-3-319-42007-3_17 | es_ES |
dc.rights | restrictedAccess | es_ES |
dc.subject | bibliometrics | es_ES |
dc.subject | H-index | es_ES |
dc.subject | science mapping | es_ES |
dc.subject | citations | es_ES |
dc.subject | WOS(2) | es_ES |
dc.subject | Scopus(2) | es_ES |
dc.title | Bibliometric Tools for Discovering Information in Database | es_ES |
dc.type | conferenceObject | es_ES |
reunir.tag | ~ARI | es_ES |
dc.identifier.doi | https://doi.org/10.1007/978-3-319-42007-3_17 |
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