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Which people use which scientific papers? An evaluation of data from F1000 and Mendeley

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  • Bornmann, Lutz
  • Haunschild, Robin

Abstract

The increased interest in an impact measurement of research on other areas of the society than research has led in scientometrics to an investigation of altmetrics. Particular attention is paid here to a targeted broad impact measurement: The aim is to discover the impact which a particular publication set has on specific user groups (outside research) by using altmetrics. This study used the Mendeley application programming interface (API) to download the Mendeley counts (broken down by different user types of publications in Mendeley) for a comprehensive F1000Prime data set. F1000Prime is a post-publication peer review system for papers from the biomedical area. As the F1000 papers are provided with tags from experts in this area (Faculty members) which can characterise a paper more exactly (such as “good for teaching” or “new finding”), the interest of different user groups in specifically tagged papers could be investigated. This study's evaluation of the variously tagged F1000 papers provided interesting insights into the use of research papers by different user groups. The most interesting tag for altmetrics research is “good for teaching”. This applies to papers which are well written and provide an overview of a topic. Papers with this tag can be expected to arouse interest among people who are hardly or not at all involved in research. The results of the regression models in this study do in fact show that lecturers, researchers at a non-academic institution, and others (such as librarians) have a special interest in this kind of papers. In the case of a key article in a field, or a particularly well written article that provides a good overview of a topic, then it will tend to be better received by people which are not particularly related to academic research.

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  • Bornmann, Lutz & Haunschild, Robin, 2015. "Which people use which scientific papers? An evaluation of data from F1000 and Mendeley," Journal of Informetrics, Elsevier, vol. 9(3), pages 477-487.
    • Handle: RePEc:eee:infome:v:9:y:2015:i:3:p:477-487
    DOI: 10.1016/j.joi.2015.04.001
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    References listed on IDEAS

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    1. Lutz Bornmann, 2015. "Letter to the Editor: On the conceptualisation and theorisation of the impact caused by publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(3), pages 1145-1148, June.
    2. Lutz Bornmann, 2013. "What is societal impact of research and how can it be assessed? a literature survey," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(2), pages 217-233, February.
    3. Mike Thelwall & Nabeil Maflahi, 2015. "Are scholarly articles disproportionately read in their own country? An analysis of mendeley readers," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(6), pages 1124-1135, June.
    4. Bornmann, Lutz, 2014. "Validity of altmetrics data for measuring societal impact: A study using data from Altmetric and F1000Prime," Journal of Informetrics, Elsevier, vol. 8(4), pages 935-950.
    5. Ulrich Kohler & Frauke Kreuter, 2009. "Data Analysis using Stata, 2nd Edition," Stata Press books, StataCorp LP, number daus2, March.
    6. Bornmann, Lutz & Williams, Richard, 2013. "How to calculate the practical significance of citation impact differences? An empirical example from evaluative institutional bibliometrics using adjusted predictions and marginal effects," Journal of Informetrics, Elsevier, vol. 7(2), pages 562-574.
    7. Xuemei Li & Mike Thelwall & Dean Giustini, 2012. "Validating online reference managers for scholarly impact measurement," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 461-471, May.
    8. Stefanie Haustein & Isabella Peters & Judit Bar-Ilan & Jason Priem & Hadas Shema & Jens Terliesner, 2014. "Coverage and adoption of altmetrics sources in the bibliometric community," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1145-1163, November.
    9. Hadas Shema & Judit Bar-Ilan & Mike Thelwall, 2014. "Do blog citations correlate with a higher number of future citations? Research blogs as a potential source for alternative metrics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(5), pages 1018-1027, May.
    10. Lutz Bornmann, 2015. "Alternative metrics in scientometrics: a meta-analysis of research into three altmetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(3), pages 1123-1144, June.
    11. Lutz Bornmann, 2015. "Interrater reliability and convergent validity of F1000Prime peer review," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(12), pages 2415-2426, December.
    12. Richard Williams, 2012. "Using the margins command to estimate and interpret adjusted predictions and marginal effects," Stata Journal, StataCorp LP, vol. 12(2), pages 308-331, June.
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    1. Bornmann, Lutz & Haunschild, Robin, 2016. "Normalization of Mendeley reader impact on the reader- and paper-side: A comparison of the mean discipline normalized reader score (MDNRS) with the mean normalized reader score (MNRS) and bare reader ," Journal of Informetrics, Elsevier, vol. 10(3), pages 776-788.
    2. Drahomira Herrmannova & Robert M. Patton & Petr Knoth & Christopher G. Stahl, 2018. "Do citations and readership identify seminal publications?," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 239-262, April.
    3. Wang, Peiling & Su, Jing, 2021. "Post-publication expert recommendations in faculty opinions (F1000Prime): Recommended articles and citations," Journal of Informetrics, Elsevier, vol. 15(3).
    4. Houqiang Yu & Xueting Cao & Tingting Xiao & Zhenyi Yang, 2020. "How accurate are policy document mentions? A first look at the role of altmetrics database," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1517-1540, November.
    5. Xianwen Wang & Zhichao Fang & Xinhui Guo, 2016. "Tracking the digital footprints to scholarly articles from social media," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1365-1376, November.
    6. Mojisola Erdt & Aarthy Nagarajan & Sei-Ching Joanna Sin & Yin-Leng Theng, 2016. "Altmetrics: an analysis of the state-of-the-art in measuring research impact on social media," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1117-1166, November.
    7. Mehrbakhsh Nilashi & Othman Ibrahim & Shamila Sohaei & Hossein Ahmadi & Alireza Almaee, 2016. "Features Influencing Researchers’ Selection of Reference Management Software," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 15(03), pages 1-23, September.
    8. Zhiqi Wang & Wolfgang Glänzel & Yue Chen, 2020. "The impact of preprints in Library and Information Science: an analysis of citations, usage and social attention indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1403-1423, November.
    9. Peiling Wang & Joshua Williams & Nan Zhang & Qiang Wu, 2020. "F1000Prime recommended articles and their citations: an exploratory study of four journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 933-955, February.

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    Keywords

    Altmetrics; Mendeley; F1000; Societal impact;
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