Altmetrics as a research specialty (Dimensions, 2005-2018)
The scientific literature on altmetrics published from 2005 to 2018 was analysed. The overall structure of the speciality's intellectual landscape is depicted through clusters of co-cited references, analysing journal and author co-citations. The 56,936 references cited in the 8,145 papers of a...
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Veröffentlicht in: | El profesional de la informacion 2019, Vol.28 (6), p.131-148 |
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description | The scientific literature on altmetrics published from 2005 to 2018 was analysed. The overall structure of the speciality's intellectual landscape is depicted through clusters of co-cited references, analysing journal and author co-citations. The 56,936 references cited in the 8,145 papers of all kinds retrieved from the Dimensions bibliographic database were included in the initial dataset used in the analysis. Pathfinder networks were generated with CiteSpace to determine the most prevalent journals and authors in the speciality. Conceptual structures were identified by co-citation clustering and latent semantic analysis. Open knowledge', altmetric collection', web indicator', assessing research', Research- Gate score', open data citation advantage', Google Scholar author citation', share data', academic tweet', Mendeley readership count' and social media metrics' were observed to be the lines of research presently favoured by specialists. Statistical indicators were calculated to determine the journals and contributors making the greatest impact. |
doi_str_mv | 10.3145/epi.2019.nov.08 |
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The overall structure of the speciality's intellectual landscape is depicted through clusters of co-cited references, analysing journal and author co-citations. The 56,936 references cited in the 8,145 papers of all kinds retrieved from the Dimensions bibliographic database were included in the initial dataset used in the analysis. Pathfinder networks were generated with CiteSpace to determine the most prevalent journals and authors in the speciality. Conceptual structures were identified by co-citation clustering and latent semantic analysis. Open knowledge', altmetric collection', web indicator', assessing research', Research- Gate score', open data citation advantage', Google Scholar author citation', share data', academic tweet', Mendeley readership count' and social media metrics' were observed to be the lines of research presently favoured by specialists. 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The overall structure of the speciality's intellectual landscape is depicted through clusters of co-cited references, analysing journal and author co-citations. The 56,936 references cited in the 8,145 papers of all kinds retrieved from the Dimensions bibliographic database were included in the initial dataset used in the analysis. Pathfinder networks were generated with CiteSpace to determine the most prevalent journals and authors in the speciality. Conceptual structures were identified by co-citation clustering and latent semantic analysis. Open knowledge', altmetric collection', web indicator', assessing research', Research- Gate score', open data citation advantage', Google Scholar author citation', share data', academic tweet', Mendeley readership count' and social media metrics' were observed to be the lines of research presently favoured by specialists. Statistical indicators were calculated to determine the journals and contributors making the greatest impact.</abstract><cop>Madrid</cop><pub>El Profesional de la información</pub><doi>10.3145/epi.2019.nov.08</doi><oclcid>1399431562</oclcid><tpages>18</tpages><oa>free_for_read</oa></addata></record> |
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source | Business Source Complete; Alma/SFX Local Collection |
subjects | Análisis de co-citación Análisis de redes de citas Autores Bibliographic data bases Bibliometrics Citas Citations Comunicación académica Espacio de citas Indicadores Informetrics Mapeo científico Redes sociales académicas Visualización de redes de citas |
title | Altmetrics as a research specialty (Dimensions, 2005-2018) |
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