IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v126y2021i8d10.1007_s11192-021-04034-6.html
   My bibliography  Save this article

Studying the characteristics of scientific communities using individual-level bibliometrics: the case of Big Data research

Author

Listed:
  • Xiaozan Lyu

    (Zhejiang University City College
    Leiden University)

  • Rodrigo Costas

    (Leiden University
    Stellenbosch University)

Abstract

Unlike most bibliometric studies focusing on publications, taking Big Data research as a case study, we introduce a novel bibliometric approach to unfold the status of a given scientific community from an individual-level perspective. We study the academic age, production, and research focus of the community of authors active in Big Data research. Artificial Intelligence (AI) is selected as a reference area for comparative purposes. Results show that the academic realm of “Big Data” is a growing topic with an expanding community of authors, particularly of new authors every year. Compared to AI, Big Data attracts authors with a longer academic age, who can be regarded to have accumulated some publishing experience before entering the community. Despite the highly skewed distribution of productivity amongst researchers in both communities, Big Data authors have higher values of both research focus and production than those of AI. Considering the community size, overall academic age, and persistence of publishing on the topic, our results support the idea of Big Data as a research topic with attractiveness for researchers. We argue that the community-focused indicators proposed in this study could be generalized to investigate the development and dynamics of other research fields and topics.

Suggested Citation

  • Xiaozan Lyu & Rodrigo Costas, 2021. "Studying the characteristics of scientific communities using individual-level bibliometrics: the case of Big Data research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6965-6987, August.
    • Handle: RePEc:spr:scient:v:126:y:2021:i:8:d:10.1007_s11192-021-04034-6
    DOI: 10.1007/s11192-021-04034-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-021-04034-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-021-04034-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nees Jan Eck & Ludo Waltman, 2017. "Citation-based clustering of publications using CitNetExplorer and VOSviewer," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 1053-1070, May.
    2. Gaule, Patrick & Piacentini, Mario, 2018. "An advisor like me? Advisor gender and post-graduate careers in science," Research Policy, Elsevier, vol. 47(4), pages 805-813.
    3. Rodrigo Costas & Thed N. van Leeuwen & María Bordons, 2010. "A bibliometric classificatory approach for the study and assessment of research performance at the individual level: The effects of age on productivity and impact," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(8), pages 1564-1581, August.
    4. Geuna, Aldo (ed.), 2015. "Global Mobility of Research Scientists," Elsevier Monographs, Elsevier, edition 1, number 9780128013960.
    5. Rodrigo Costas & Thed N. van Leeuwen & María Bordons, 2010. "A bibliometric classificatory approach for the study and assessment of research performance at the individual level: The effects of age on productivity and impact," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(8), pages 1564-1581, August.
    6. Nane, Gabriela F. & Larivière, Vincent & Costas, Rodrigo, 2017. "Predicting the age of researchers using bibliometric data," Journal of Informetrics, Elsevier, vol. 11(3), pages 713-729.
    7. Vivek Kumar Singh & Sumit Kumar Banshal & Khushboo Singhal & Ashraf Uddin, 2015. "Scientometric mapping of research on ‘Big Data’," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(2), pages 727-741, November.
    8. Levin, Sharon G & Stephan, Paula E, 1991. "Research Productivity over the Life Cycle: Evidence for Academic Scientists," American Economic Review, American Economic Association, vol. 81(1), pages 114-132, March.
    9. Geuna, Aldo & Shibayama, Sotaro, 2015. "Moving Out Of Academic Research: Why Scientists Stop Doing Research?," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201501, University of Turin.
    10. Jiming Hu & Yin Zhang, 2017. "Discovering the interdisciplinary nature of Big Data research through social network analysis and visualization," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 91-109, July.
    11. Alan Filipe Santana & Marcos André Gonçalves & Alberto H. F. Laender & Anderson A. Ferreira, 2017. "Incremental author name disambiguation by exploiting domain-specific heuristics," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(4), pages 931-945, April.
    12. Kasia Zalewska-Kurek & Peter A T M Geurts & Hans E Roosendaal, 2010. "The impact of the autonomy and interdependence of individual researchers on their production of knowledge and its impact: an empirical study of a nanotechnology institute," Research Evaluation, Oxford University Press, vol. 19(3), pages 217-225, September.
    13. Ludo Waltman & Nees Jan van Eck, 2012. "A new methodology for constructing a publication‐level classification system of science," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    14. Ruiz-Castillo, Javier & Costas, Rodrigo, 2014. "The skewness of scientific productivity," Journal of Informetrics, Elsevier, vol. 8(4), pages 917-934.
    15. Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Di Costa, 2018. "The effects of gender, age and academic rank on research diversification," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 373-387, February.
    16. Jinseok Kim, 2018. "Evaluating author name disambiguation for digital libraries: a case of DBLP," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1867-1886, September.
    17. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    18. Lorna Wildgaard & Jesper W. Schneider & Birger Larsen, 2014. "A review of the characteristics of 108 author-level bibliometric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 125-158, October.
    19. Ashraf Uddin & Vivek Kumar Singh & David Pinto & Ivan Olmos, 2015. "Scientometric mapping of computer science research in Mexico," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(1), pages 97-114, October.
    20. Ludo Waltman & Nees Jan Eck, 2012. "A new methodology for constructing a publication-level classification system of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    21. Yufang Peng & Jin Shi & Marcelo Fantinato & Jing Chen, 2017. "A study on the author collaboration network in big data," Information Systems Frontiers, Springer, vol. 19(6), pages 1329-1342, December.
    22. Yves Gingras & Vincent Larivière & Benoît Macaluso & Jean-Pierre Robitaille, 2008. "The Effects of Aging on Researchers' Publication and Citation Patterns," PLOS ONE, Public Library of Science, vol. 3(12), pages 1-8, December.
    23. Lutz Bornmann & Werner Marx, 2014. "How to evaluate individual researchers working in the natural and life sciences meaningfully? A proposal of methods based on percentiles of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 487-509, January.
    24. Rørstad, Kristoffer & Aksnes, Dag W., 2015. "Publication rate expressed by age, gender and academic position – A large-scale analysis of Norwegian academic staff," Journal of Informetrics, Elsevier, vol. 9(2), pages 317-333.
    25. Ying Huang & Jannik Schuehle & Alan L. Porter & Jan Youtie, 2015. "A systematic method to create search strategies for emerging technologies based on the Web of Science: illustrated for ‘Big Data’," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2005-2022, December.
    26. Rodrigo Costas & María Bordons, 2011. "Do age and professional rank influence the order of authorship in scientific publications? Some evidence from a micro-level perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 145-161, July.
    27. John Rigby & Keith Julian & Derrick F Ball, 2008. "Characterisation and measurement methods for author productivity and research vitality: a study of the R&D management field," Research Evaluation, Oxford University Press, vol. 17(1), pages 59-69, March.
    28. Giovanni Abramo & Ciriaco Andrea D’Angelo, 2011. "National-scale research performance assessment at the individual level," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(2), pages 347-364, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vincent Larivière & Rodrigo Costas, 2016. "How Many Is Too Many? On the Relationship between Research Productivity and Impact," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-10, September.
    2. Marek Kwiek & Wojciech Roszka, 2022. "Academic vs. biological age in research on academic careers: a large-scale study with implications for scientifically developing systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3543-3575, June.
    3. Ruiz-Castillo, Javier & Costas, Rodrigo, 2014. "The skewness of scientific productivity," Journal of Informetrics, Elsevier, vol. 8(4), pages 917-934.
    4. Leydesdorff, Loet & Bornmann, Lutz & Zhou, Ping, 2016. "Construction of a pragmatic base line for journal classifications and maps based on aggregated journal-journal citation relations," Journal of Informetrics, Elsevier, vol. 10(4), pages 902-918.
    5. Daiji Kawaguchi & Ayako Kondo & Keiji Saito, 2016. "Researchers’ career transitions over the life cycle," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1435-1454, December.
    6. Balázs Győrffy & Gyöngyi Csuka & Péter Herman & Ádám Török, 2020. "Is there a golden age in publication activity?—an analysis of age-related scholarly performance across all scientific disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1081-1097, August.
    7. Vîiu, Gabriel-Alexandru, 2017. "Disaggregated research evaluation through median-based characteristic scores and scales: a comparison with the mean-based approach," Journal of Informetrics, Elsevier, vol. 11(3), pages 748-765.
    8. Carusi, Chiara & Bianchi, Giuseppe, 2019. "Scientific community detection via bipartite scholar/journal graph co-clustering," Journal of Informetrics, Elsevier, vol. 13(1), pages 354-386.
    9. Zharova, Alona & Härdle, Wolfgang Karl & Lessmann, Stefan, 2017. "Is scientific performance a function of funds?," SFB 649 Discussion Papers 2017-028, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. 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).
    11. Alona Zharova & Wolfgang K. Härdle & Stefan Lessmann, 2017. "Is Scientific Performance a Function of Funds?," SFB 649 Discussion Papers SFB649DP2017-028, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Linda Reijnhoudt & Rodrigo Costas & Ed Noyons & Katy Börner & Andrea Scharnhorst, 2014. "‘Seed + expand’: a general methodology for detecting publication oeuvres of individual researchers," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1403-1417, November.
    13. Díaz-Faes, Adrián A. & Costas, Rodrigo & Galindo, M. Purificación & Bordons, María, 2015. "Unravelling the performance of individual scholars: Use of Canonical Biplot analysis to explore the performance of scientists by academic rank and scientific field," Journal of Informetrics, Elsevier, vol. 9(4), pages 722-733.
    14. Paola Bernardi & Alberto Bertello & Canio Forliano & Ludovico Bullini Orlandi, 2022. "Beyond the “ivory tower”. Comparing academic and non-academic knowledge on social entrepreneurship," International Entrepreneurship and Management Journal, Springer, vol. 18(3), pages 999-1032, September.
    15. Sixto-Costoya Andrea & Robinson-Garcia Nicolas & Leeuwen Thed & Costas Rodrigo, 2021. "Exploring the relevance of ORCID as a source of study of data sharing activities at the individual-level: a methodological discussion," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 7149-7165, August.
    16. Juan Pablo Bascur & Suzan Verberne & Nees Jan Eck & Ludo Waltman, 2023. "Academic information retrieval using citation clusters: in-depth evaluation based on systematic reviews," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2895-2921, May.
    17. Zharova, Alona & Härdle, Wolfgang Karl & Lessmann, Stefan, 2023. "Data-driven support for policy and decision-making in university research management: A case study from Germany," European Journal of Operational Research, Elsevier, vol. 308(1), pages 353-368.
    18. Shuo Xu & Junwan Liu & Dongsheng Zhai & Xin An & Zheng Wang & Hongshen Pang, 2018. "Overlapping thematic structures extraction with mixed-membership stochastic blockmodel," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 61-84, October.
    19. Zhang, Yi & Huang, Ying & Porter, Alan L. & Zhang, Guangquan & Lu, Jie, 2019. "Discovering and forecasting interactions in big data research: A learning-enhanced bibliometric study," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 795-807.
    20. Tuba Bircan & Almila Alkim Akdag Salah, 2022. "A Bibliometric Analysis of the Use of Artificial Intelligence Technologies for Social Sciences," Mathematics, MDPI, vol. 10(23), pages 1-17, November.

    More about this item

    Keywords

    Scientific community; Big Data research; Production; Research focus;
    All these keywords.

    JEL classification:

    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:126:y:2021:i:8:d:10.1007_s11192-021-04034-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.