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An extensive analysis of the presence of altmetric data for Web of Science publications across subject fields and research topics
Sufficient data presence is one of the key preconditions for applying metrics in practice. Based on both Altmetric.com data and Mendeley data collected up to 2019, this paper presents a state-of-the-art analysis of the presence of 12 kinds of altmetric events for nearly 12.3 million Web of Science p...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297939/ https://www.ncbi.nlm.nih.gov/pubmed/32836523 http://dx.doi.org/10.1007/s11192-020-03564-9 |
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author | Fang, Zhichao Costas, Rodrigo Tian, Wencan Wang, Xianwen Wouters, Paul |
author_facet | Fang, Zhichao Costas, Rodrigo Tian, Wencan Wang, Xianwen Wouters, Paul |
author_sort | Fang, Zhichao |
collection | PubMed |
description | Sufficient data presence is one of the key preconditions for applying metrics in practice. Based on both Altmetric.com data and Mendeley data collected up to 2019, this paper presents a state-of-the-art analysis of the presence of 12 kinds of altmetric events for nearly 12.3 million Web of Science publications published between 2012 and 2018. Results show that even though an upward trend of data presence can be observed over time, except for Mendeley readers and Twitter mentions, the overall presence of most altmetric data is still low. The majority of altmetric events go to publications in the fields of Biomedical and Health Sciences, Social Sciences and Humanities, and Life and Earth Sciences. As to research topics, the level of attention received by research topics varies across altmetric data, and specific altmetric data show different preferences for research topics, on the basis of which a framework for identifying hot research topics is proposed and applied to detect research topics with higher levels of attention garnered on certain altmetric data source. Twitter mentions and policy document citations were selected as two examples to identify hot research topics of interest of Twitter users and policy-makers, respectively, shedding light on the potential of altmetric data in monitoring research trends of specific social attention. |
format | Online Article Text |
id | pubmed-7297939 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-72979392020-06-17 An extensive analysis of the presence of altmetric data for Web of Science publications across subject fields and research topics Fang, Zhichao Costas, Rodrigo Tian, Wencan Wang, Xianwen Wouters, Paul Scientometrics Article Sufficient data presence is one of the key preconditions for applying metrics in practice. Based on both Altmetric.com data and Mendeley data collected up to 2019, this paper presents a state-of-the-art analysis of the presence of 12 kinds of altmetric events for nearly 12.3 million Web of Science publications published between 2012 and 2018. Results show that even though an upward trend of data presence can be observed over time, except for Mendeley readers and Twitter mentions, the overall presence of most altmetric data is still low. The majority of altmetric events go to publications in the fields of Biomedical and Health Sciences, Social Sciences and Humanities, and Life and Earth Sciences. As to research topics, the level of attention received by research topics varies across altmetric data, and specific altmetric data show different preferences for research topics, on the basis of which a framework for identifying hot research topics is proposed and applied to detect research topics with higher levels of attention garnered on certain altmetric data source. Twitter mentions and policy document citations were selected as two examples to identify hot research topics of interest of Twitter users and policy-makers, respectively, shedding light on the potential of altmetric data in monitoring research trends of specific social attention. Springer International Publishing 2020-06-17 2020 /pmc/articles/PMC7297939/ /pubmed/32836523 http://dx.doi.org/10.1007/s11192-020-03564-9 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Fang, Zhichao Costas, Rodrigo Tian, Wencan Wang, Xianwen Wouters, Paul An extensive analysis of the presence of altmetric data for Web of Science publications across subject fields and research topics |
title | An extensive analysis of the presence of altmetric data for Web of Science publications across subject fields and research topics |
title_full | An extensive analysis of the presence of altmetric data for Web of Science publications across subject fields and research topics |
title_fullStr | An extensive analysis of the presence of altmetric data for Web of Science publications across subject fields and research topics |
title_full_unstemmed | An extensive analysis of the presence of altmetric data for Web of Science publications across subject fields and research topics |
title_short | An extensive analysis of the presence of altmetric data for Web of Science publications across subject fields and research topics |
title_sort | extensive analysis of the presence of altmetric data for web of science publications across subject fields and research topics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297939/ https://www.ncbi.nlm.nih.gov/pubmed/32836523 http://dx.doi.org/10.1007/s11192-020-03564-9 |
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