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      Towards a second generation of ‘social media metrics’: Characterizing Twitter communities of attention around science

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          Abstract

          ‘Social media metrics’ are bursting into science studies as emerging new measures of impact related to scholarly activities. However, their meaning and scope as scholarly metrics is still far from being grasped. This research seeks to shift focus from the consideration of social media metrics around science as mere indicators confined to the analysis of the use and visibility of publications on social media to their consideration as metrics of interaction and circulation of scientific knowledge across different communities of attention, and particularly as metrics that can also be used to characterize these communities. Although recent research efforts have proposed tentative typologies of social media users, no study has empirically examined the full range of Twitter user’s behavior within Twitter and disclosed the latent dimensions in which activity on Twitter around science can be classified. To do so, we draw on the overall activity of social media users on Twitter interacting with research objects collected from the Altmetic.com database. Data from over 1.3 million unique users, accounting for over 14 million tweets to scientific publications, is analyzed. Based on an exploratory and confirmatory factor analysis, four latent dimensions are identified: ‘Science Engagement’, ‘Social Media Capital’, ‘Social Media Activity’ and ‘Science Focus’. Evidence on the predominant type of users by each of the four dimensions is provided by means of VOSviewer term maps of Twitter profile descriptions. This research breaks new ground for the systematic analysis and characterization of social media users’ activity around science.

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

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            Characterizing Social Media Metrics of Scholarly Papers: The Effect of Document Properties and Collaboration Patterns

            A number of new metrics based on social media platforms—grouped under the term “altmetrics”—have recently been introduced as potential indicators of research impact. Despite their current popularity, there is a lack of information regarding the determinants of these metrics. Using publication and citation data from 1.3 million papers published in 2012 and covered in Thomson Reuters’ Web of Science as well as social media counts from Altmetric.com, this paper analyses the main patterns of five social media metrics as a function of document characteristics (i.e., discipline, document type, title length, number of pages and references) and collaborative practices and compares them to patterns known for citations. Results show that the presence of papers on social media is low, with 21.5% of papers receiving at least one tweet, 4.7% being shared on Facebook, 1.9% mentioned on blogs, 0.8% found on Google+ and 0.7% discussed in mainstream media. By contrast, 66.8% of papers have received at least one citation. Our findings show that both citations and social media metrics increase with the extent of collaboration and the length of the references list. On the other hand, while editorials and news items are seldom cited, it is these types of document that are the most popular on Twitter. Similarly, while longer papers typically attract more citations, an opposite trend is seen on social media platforms. Finally, contrary to what is observed for citations, it is papers in the Social Sciences and humanities that are the most often found on social media platforms. On the whole, these findings suggest that factors driving social media and citations are different. Therefore, social media metrics cannot actually be seen as alternatives to citations; at most, they may function as complements to other type of indicators.
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              Assessing basic research

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: 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
                22 May 2019
                2019
                : 14
                : 5
                : e0216408
                Affiliations
                [1 ] INGENIO (CSIC-UPV), Universitat Politécnica de València, Valencia, Spain
                [2 ] School of Information Sciences, Wayne State University, Detroit, Michigan, United States of America
                [3 ] Centre for Science and Technology Studies (CWTS), Leiden University, Leiden, The Netherlands
                [4 ] Centre for Research on Evaluation, Science and Technology (CREST), Stellenbosch University, Stellenbosch, South Africa
                Max Planck Society, GERMANY
                Author notes

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

                Author information
                http://orcid.org/0000-0003-1928-4608
                Article
                PONE-D-18-33837
                10.1371/journal.pone.0216408
                6530891
                31116783
                c012fddc-bc6a-4b24-908c-5d52ac7de025
                © 2019 Díaz-Faes et al

                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
                : 26 November 2018
                : 21 April 2019
                Page count
                Figures: 2, Tables: 4, Pages: 18
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100010198, Ministerio de Economía, Industria y Competitividad, Gobierno de España;
                Award ID: Juan de la Cierva Postdoctoral Grant (FJCI-2015-23699)
                Award Recipient :
                Funded by: South African DST-NRF Centre of Excellence in Scientometrics
                Award Recipient :
                Funded by: Science, Technology and Innovation Policy (SciSTIP)
                Award Recipient :
                AADF is currently supported by a Juan de la Cierva-Formación postdoctoral grant (FJCI-2015-23699) from the Spanish Ministry of Economy and Competitiveness and benefited from a visiting stay at the Centre for Science and Technology Studies (CWTS) funded by the 'Call for visit to RISIS Facilities' – Research Infrastructure for Science and Innovation Policy Studies, in February 2018. RC was partially funded by the South African DST-NRF Centre of Excellence in Scientometrics and Science, Technology and Innovation Policy (SciSTIP). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                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
                Social Sciences
                Sociology
                Communications
                Social Communication
                Social Media
                Computer and Information Sciences
                Network Analysis
                Social Networks
                Social Media
                Social Sciences
                Sociology
                Social Networks
                Social Media
                Social Sciences
                Sociology
                Social Research
                Social Sciences
                Sociology
                Communications
                Social Communication
                Social Media
                Facebook
                Computer and Information Sciences
                Network Analysis
                Social Networks
                Social Media
                Facebook
                Social Sciences
                Sociology
                Social Networks
                Social Media
                Facebook
                Research and Analysis Methods
                Research Assessment
                Altmetrics
                Research and Analysis Methods
                Research Assessment
                Scientometrics
                Research and Analysis Methods
                Research Assessment
                Bibliometrics
                Research and Analysis Methods
                Research Assessment
                Research Quality Assessment
                Custom metadata
                Data are available from figshare ( https://doi.org/10.6084/m9.figshare.7718720.v1). PHP script to retrieve tweets from Twitter API is available from: https://github.com/tdbowman/retrieveTweets.

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