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Measuring field-normalized impact of papers on specific societal groups: An altmetrics study based on Mendeley Data

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  • Lutz Bornmann
  • Robin Haunschild

Abstract

Bibliometrics is successful in measuring impact because the target is clearly defined: the publishing scientist who is still active and working. Thus, citations are a target-oriented metric which measures impact on science. In contrast, societal impact measurements based on altmetrics are as a rule intended to measure impact in a broad sense on all areas of society (e.g. science, culture, politics, and economics). This tendency is especially reflected in the efforts to design composite indicators (e.g. the Altmetric Attention Score). We deem appropriate that not only the impact measurement using citations is target-oriented (citations measure the impact of papers on scientists) but also the measurement of impact using altmetrics. Impact measurements only make sense, if the target group—the recipient of academic papers—is clearly defined. Thus, we extend in this study the field-normalized reader impact indicator proposed by us in an earlier study, which is based on Mendeley data (the mean normalized reader score, MNRS), to a target-oriented field-normalized impact indicator (e.g. MNRSED measures reader impact on the sector of educational donation, i.e. teaching). This indicator can show—as demonstrated in empirical examples—the ability of journals, countries, and academic institutions to publish papers which are below or above the average impact of papers on a specific sector in society (e.g. the educational or teaching sector). Thus, the method allows to measure the impact of scientific papers on certain groups—controlling for the field in which the papers have been published and their publication year.

Suggested Citation

  • Lutz Bornmann & Robin Haunschild, 2017. "Measuring field-normalized impact of papers on specific societal groups: An altmetrics study based on Mendeley Data," Research Evaluation, Oxford University Press, vol. 26(3), pages 230-241.
  • Handle: RePEc:oup:rseval:v:26:y:2017:i:3:p:230-241.
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    Citations

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    Cited by:

    1. Robin Haunschild & Lutz Bornmann, 2018. "Field- and time-normalization of data with many zeros: an empirical analysis using citation and Twitter data," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 997-1012, August.
    2. Stina Hansson & Merritt Polk, 2018. "Assessing the impact of transdisciplinary research: The usefulness of relevance, credibility, and legitimacy for understanding the link between process and impact," Research Evaluation, Oxford University Press, vol. 27(2), pages 132-144.
    3. Liwei Zhang & Jue Wang, 2021. "What affects publications’ popularity on Twitter?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 9185-9198, November.
    4. Bornmann, Lutz & Haunschild, Robin & Adams, Jonathan, 2019. "Do altmetrics assess societal impact in a comparable way to case studies? An empirical test of the convergent validity of altmetrics based on data from the UK research excellence framework (REF)," Journal of Informetrics, Elsevier, vol. 13(1), pages 325-340.
    5. Lutz Bornmann & Rüdiger Mutz & Robin Haunschild & Felix Moya-Anegon & Mirko Almeida Madeira Clemente & Moritz Stefaner, 2021. "Mapping the impact of papers on various status groups in excellencemapping.net: a new release of the excellence mapping tool based on citation and reader scores," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 9305-9331, November.
    6. Alberto Cerezo-Narváez & Andrés Pastor-Fernández & Manuel Otero-Mateo & Pablo Ballesteros-Pérez, 2022. "The Influence of Knowledge on Managing Risk for the Success in Complex Construction Projects: The IPMA Approach," Sustainability, MDPI, vol. 14(15), pages 1-30, August.
    7. Juan Miguel Campanario, 2018. "Journals that Rise from the Fourth Quartile to the First Quartile in Six Years or Less: Mechanisms of Change and the Role of Journal Self-Citations," Publications, MDPI, vol. 6(4), pages 1-15, November.
    8. Zhichao Fang & Rodrigo Costas & Wencan Tian & Xianwen Wang & Paul Wouters, 2020. "An extensive analysis of the presence of altmetric data for Web of Science publications across subject fields and research topics," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2519-2549, September.

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