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      Do altmetrics correlate with the quality of papers? A large-scale empirical study based on F1000Prime data

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      PLoS ONE
      Public Library of Science

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          Abstract

          In this study, we address the question whether (and to what extent, respectively) altmetrics are related to the scientific quality of papers (as measured by peer assessments). Only a few studies have previously investigated the relationship between altmetrics and assessments by peers. In the first step, we analyse the underlying dimensions of measurement for traditional metrics (citation counts) and altmetrics–by using principal component analysis (PCA) and factor analysis (FA). In the second step, we test the relationship between the dimensions and quality of papers (as measured by the post-publication peer-review system of F1000Prime assessments)–using regression analysis. The results of the PCA and FA show that altmetrics operate along different dimensions, whereas Mendeley counts are related to citation counts, and tweets form a separate dimension. The results of the regression analysis indicate that citation-based metrics and readership counts are significantly more related to quality, than tweets. This result on the one hand questions the use of Twitter counts for research evaluation purposes and on the other hand indicates potential use of Mendeley reader counts.

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          Scholarly use of social media and altmetrics: A review of the literature

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            Do altmetrics point to the broader impact of research? An overview of benefits and disadvantages of altmetrics

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              Alternative metrics in scientometrics: a meta-analysis of research into three altmetrics

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                23 May 2018
                2018
                : 13
                : 5
                : e0197133
                Affiliations
                [1 ] Division for Science and Innovation Studies, Administrative Headquarters of the Max Planck Society, Munich, Germany
                [2 ] Max Planck Institute for Solid State Research, Stuttgart, Germany
                Universidad de las Palmas de Gran Canaria, SPAIN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-0810-7091
                Article
                PONE-D-18-05457
                10.1371/journal.pone.0197133
                5965816
                29791468
                3a22b925-f85d-45dd-9597-83a5c7c8d524
                © 2018 Bornmann, Haunschild

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 19 February 2018
                : 26 April 2018
                Page count
                Figures: 0, Tables: 6, Pages: 12
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Research and Analysis Methods
                Research Assessment
                Altmetrics
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Multivariate Analysis
                Principal Component Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Multivariate Analysis
                Principal Component Analysis
                Research and Analysis Methods
                Research Assessment
                Citation Analysis
                Social Sciences
                Sociology
                Communications
                Social Communication
                Social Media
                Twitter
                Computer and Information Sciences
                Network Analysis
                Social Networks
                Social Media
                Twitter
                Social Sciences
                Sociology
                Social Networks
                Social Media
                Twitter
                Research and Analysis Methods
                Research Assessment
                Bibliometrics
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Factor Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Factor Analysis
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Regression Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Regression Analysis
                Research and Analysis Methods
                Research Assessment
                Research Quality Assessment
                Custom metadata
                The complete dataset excluding DOIs have been made available at https://doi.org/10.6084/m9.figshare.6120158.v1.

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                Uncategorized

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