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Personalizing papers using Altmetrics: comparing paper ‘Quality’ or ‘Impact’ to person ‘Intelligence’ or ‘Personality’

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  • Brett Buttliere

    (Leibniz-Institut fur Wissensmedien)

  • Jürgen Buder

    (Leibniz-Institut fur Wissensmedien)

Abstract

Despite their important position in the research environment, there is a growing theoretical uncertainty concerning what research metrics indicate (e.g., quality, impact, attention). Here we utilize the same tools used to study latent traits like Intelligence and Personality to get a quantitative understanding of what over 20 common research metrics indicate about the papers they represent. The sample is all of the 32,962 papers PLoS published in 2014, with results suggesting that there are at least two important underlying factors, which could generally be described as Scientific Attention/Discussion (citations), General Attention/Discussion (views, tweets), and potentially Media Attention/Discussion (media mentions). The General Attention metric is correlated about .50 with both the Academic and Media factors, though the Academic and Media attention are only correlated with each other below .05. The overall best indicator of the dataset was the total lifetime views on the paper, which is also probably the easiest to game. The results indicate the need for funding bodies to decide what they value and how to measure it (e.g., types of attention, quality).

Suggested Citation

  • Brett Buttliere & Jürgen Buder, 2017. "Personalizing papers using Altmetrics: comparing paper ‘Quality’ or ‘Impact’ to person ‘Intelligence’ or ‘Personality’," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 219-239, April.
  • Handle: RePEc:spr:scient:v:111:y:2017:i:1:d:10.1007_s11192-017-2246-9
    DOI: 10.1007/s11192-017-2246-9
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    References listed on IDEAS

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    1. Lutz Bornmann, 2016. "What do altmetrics counts mean? A plea for content analyses," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(4), pages 1016-1017, April.
    2. Fairclough, Ruth & Thelwall, Mike, 2015. "National research impact indicators from Mendeley readers," Journal of Informetrics, Elsevier, vol. 9(4), pages 845-859.
    3. Johan Bollen & Herbert Van de Sompel & Aric Hagberg & Ryan Chute, 2009. "A Principal Component Analysis of 39 Scientific Impact Measures," PLOS ONE, Public Library of Science, vol. 4(6), pages 1-11, June.
    4. Hajar Sotudeh & Zahra Mazarei & Mahdieh Mirzabeigi, 2015. "CiteULike bookmarks are correlated to citations at journal and author levels in library and information science," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2237-2248, December.
    5. Rodrigo Costas & Zohreh Zahedi & Paul Wouters, 2015. "Do “altmetrics” correlate with citations? Extensive comparison of altmetric indicators with citations from a multidisciplinary perspective," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(10), pages 2003-2019, October.
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    Cited by:

    1. Vahid Garousi & João M. Fernandes, 2017. "Quantity versus impact of software engineering papers: a quantitative study," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(2), pages 963-1006, August.
    2. Thelwall, Mike & Nevill, Tamara, 2018. "Could scientists use Altmetric.com scores to predict longer term citation counts?," Journal of Informetrics, Elsevier, vol. 12(1), pages 237-248.
    3. Dimity Stephen & Stephan Stahlschmidt, 2024. "Contrasting cross-correlation: Meta-analyses of the associations between citations and 13 altmetrics, incorporating moderating variables," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(10), pages 6049-6063, October.

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