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Do Altmetrics Work? Twitter and Ten Other Social Web Services

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      Altmetric measurements derived from the social web are increasingly advocated and used as early indicators of article impact and usefulness. Nevertheless, there is a lack of systematic scientific evidence that altmetrics are valid proxies of either impact or utility although a few case studies have reported medium correlations between specific altmetrics and citation rates for individual journals or fields. To fill this gap, this study compares 11 altmetrics with Web of Science citations for 76 to 208,739 PubMed articles with at least one altmetric mention in each case and up to 1,891 journals per metric. It also introduces a simple sign test to overcome biases caused by different citation and usage windows. Statistically significant associations were found between higher metric scores and higher citations for articles with positive altmetric scores in all cases with sufficient evidence (Twitter, Facebook wall posts, research highlights, blogs, mainstream media and forums) except perhaps for Google+ posts. Evidence was insufficient for LinkedIn, Pinterest, question and answer sites, and Reddit, and no conclusions should be drawn about articles with zero altmetric scores or the strength of any correlation between altmetrics and citations. Nevertheless, comparisons between citations and metric values for articles published at different times, even within the same year, can remove or reverse this association and so publishers and scientometricians should consider the effect of time when using altmetrics to rank articles. Finally, the coverage of all the altmetrics except for Twitter seems to be low and so it is not clear if they are prevalent enough to be useful in practice.

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      Author and article information

      [1 ]School of Technology, University of Wolverhampton, Wolverhampton, United Kingdom
      [2 ]École de bibliothéconomie et des sciences de l’information, Université de Montréal, Montréal, Québec, Canada and Science-Metrix Inc., Montréal, Québec, Canada
      [3 ]École de bibliothéconomie et des sciences de l’information, Université de Montréal, Montréal, Québec, Canada and Observatoire des sciences et des technologies, Centre interuniversitaire de recherche sur la science et la technologie, Université du Québec à Montréal, Montréal, Québec, Canada
      [4 ]School of Information and Library Science, Indiana University Bloomington, Bloomington, Indiana, United States of America
      Max Planck Society, Germany
      Author notes

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

      Conceived and designed the experiments: MT VL CRS. Performed the experiments: MT. Analyzed the data: MT. Wrote the paper: MT SH VL CRS.

      Role: Editor
      PLoS One
      PLoS ONE
      PLoS ONE
      Public Library of Science (San Francisco, USA )
      28 May 2013
      : 8
      : 5
      23724101 3665624 PONE-D-13-08281 10.1371/journal.pone.0064841

      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.

      Pages: 7
      This research was part of the international Digging into Data program (funded by Arts and Humanities Research Council/Economic and Social Research Council/Joint Information Systems Committee (United Kingdom), Social Sciences and Humanities Research Council (Canada), and the National Science Foundation (United States; grant #1208804). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
      Research Article
      Computer Science
      Information Technology
      Text Mining
      Science Policy
      Research Assessment
      Publication Practices
      Research Monitoring
      Social and Behavioral Sciences
      Information Science
      Information Storage and Retrieval
      Social Networks



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