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Research portfolio analysis and topic prominence

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  • Klavans, Richard
  • Boyack, Kevin W.

Abstract

Stakeholders in the science system need to decide where to place their bets. Example questions include: Which areas of research should get more funding? Who should we hire? Which projects should we abandon and which new projects should we start? Making informed choices requires knowledge about these research options. Unfortunately, to date research portfolio options have not been defined in a consistent, transparent and relevant manner. Furthermore, we don’t know how to define demand for these options. In this article, we address the issues of consistency, transparency, relevance and demand by using a model of science consisting of 91,726 topics (or research options) that contain over 58 million documents. We present a new indicator of topic prominence – a measure of visibility, momentum and, ultimately, demand. We assign over $203 billion of project-level funding data from STAR METRICS® to individual topics in science, and show that the indicator of topic prominence, explains over one-third of the variance in current (or future) funding by topic. We also show that highly prominent topics receive far more funding per researcher than topics that are not prominent. Implications of these results for research planning and portfolio analysis by institutions and researchers are emphasized.

Suggested Citation

  • Klavans, Richard & Boyack, Kevin W., 2017. "Research portfolio analysis and topic prominence," Journal of Informetrics, Elsevier, vol. 11(4), pages 1158-1174.
    • Handle: RePEc:eee:infome:v:11:y:2017:i:4:p:1158-1174
    DOI: 10.1016/j.joi.2017.10.002
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    Citations

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    Cited by:

    1. Matthias Held & Grit Laudel & Jochen Gläser, 2021. "Challenges to the validity of topic reconstruction," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4511-4536, May.
    2. Lucília Cardoso & Arthur Filipe Araújo & Luís Lima Santos & Roland Schegg & Zélia Breda & Carlos Costa, 2021. "Country Performance Analysis of Swiss Tourism, Leisure and Hospitality Management Research," Sustainability, MDPI, vol. 13(4), pages 1-24, February.
    3. Kosyakov, Denis & Pislyakov, Vladimir, 2024. "“I'd like to publish in Q1, but there's no Q1 to be found”: Study of journal quartile distributions across subject categories and topics," Journal of Informetrics, Elsevier, vol. 18(1).
    4. Xu, Haiyun & Winnink, Jos & Yue, Zenghui & Liu, Ziqiang & Yuan, Guoting, 2020. "Topic-linked innovation paths in science and technology," Journal of Informetrics, Elsevier, vol. 14(2).
    5. Lucília Cardoso & Rui Silva & Giovana Goretti Feijó de Almeida & Luís Lima Santos, 2020. "A Bibliometric Model to Analyze Country Research Performance: SciVal Topic Prominence Approach in Tourism, Leisure and Hospitality," Sustainability, MDPI, vol. 12(23), pages 1-26, November.
    6. Yuanyuan Shang & Gunnar Sivertsen & Zhe Cao & Lin Zhang, 2022. "Gender differences among first authors in research focused on the Sustainable Development Goal of Gender Equality," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4769-4796, August.
    7. Shu, Fei & Julien, Charles-Antoine & Zhang, Lin & Qiu, Junping & Zhang, Jing & Larivière, Vincent, 2019. "Comparing journal and paper level classifications of science," Journal of Informetrics, Elsevier, vol. 13(1), pages 202-225.
    8. Edgar D. Zanotto & Vinicius Carvalho, 2021. "Article age- and field-normalized tools to evaluate scientific impact and momentum," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2865-2883, April.
    9. Takahiro Kawamura & Katsutaro Watanabe & Naoya Matsumoto & Shusaku Egami & Mari Jibu, 2018. "Funding map using paragraph embedding based on semantic diversity," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 941-958, August.
    10. Pei-Shan Chi & Stijn Conix, 2022. "Measuring the isolation of research topics in philosophy," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 1669-1696, April.
    11. Mila Cascajares & Alfredo Alcayde & Esther Salmerón-Manzano & Francisco Manzano-Agugliaro, 2021. "The Bibliometric Literature on Scopus and WoS: The Medicine and Environmental Sciences Categories as Case of Study," IJERPH, MDPI, vol. 18(11), pages 1-31, May.
    12. Kevin W. Boyack & Caleb Smith & Richard Klavans, 2018. "Toward predicting research proposal success," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 449-461, February.
    13. Ugo Moschini & Elena Fenialdi & Cinzia Daraio & Giancarlo Ruocco & Elisa Molinari, 2020. "A comparison of three multidisciplinarity indices based on the diversity of Scopus subject areas of authors’ documents, their bibliography and their citing papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1145-1158, November.
    14. Muñoz-Écija, Teresa & Vargas-Quesada, Benjamín & Chinchilla Rodríguez, Zaida, 2019. "Coping with methods for delineating emerging fields: Nanoscience and nanotechnology as a case study," Journal of Informetrics, Elsevier, vol. 13(4).
    15. Keisuke Okamura, 2019. "Interdisciplinarity revisited: evidence for research impact and dynamism," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-9, December.
    16. Madsen, Emil Bargmann & Aagaard, Kaare, 2020. "Concentration of Danish research funding on individual researchers and research topics: Patterns and potential drivers," SocArXiv j874c, Center for Open Science.
    17. Luís Lima Santos & Lucília Cardoso & Noelia Araújo-Vila & Jose A. Fraiz-Brea, 2020. "Sustainability Perceptions in Tourism and Hospitality: A Mixed-Method Bibliometric Approach," Sustainability, MDPI, vol. 12(21), pages 1-18, October.
    18. Ma, Yinghong & Song, Le & Ji, Zhaoxun & Wang, Qian & Yu, Qinglin, 2020. "Scholar’s career switch adhesive with research topics: An evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).

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