IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v129y2024i11d10.1007_s11192-024-05161-6.html
   My bibliography  Save this article

Comparative science mapping: a novel conceptual structure analysis with metadata

Author

Listed:
  • Massimo Aria

    (University of Naples Federico II
    K-Synth)

  • Corrado Cuccurullo

    (University of Campania L. Vanvitelli
    K-Synth)

  • Luca D’Aniello

    (University of Naples Federico II
    K-Synth)

  • Michelangelo Misuraca

    (University of Calabria
    K-Synth)

  • Maria Spano

    (University of Naples Federico II
    K-Synth)

Abstract

Textual analyses on scientific publications are increasingly employed in Bibliometrics to explore the conceptual structure of a research domain, often overlooking other rich metadata that can provide deeper insights into the scientific landscape of reference. This paper introduces an innovative technique to explore the conceptual structure of different observation units in a joint representation. The proposed strategy segments bibliographic datasets based on several metadata dimensions, such as the authors (and their characteristics), the corresponding institutions, or their geographical localisation. It provides detailed maps that depict multiple conceptual frameworks, allowing for detailed comparisons and insights in a joint visualisation. We employed these strategic diagrams to visualise and analyse the oncological research of Italian Academic Medical Centres (AMCs), particularly focusing on public institutions. The analysis focuses on how different AMCs specialise and interact, providing a comparative framework that aids AMCs themselves in directing their research strategies toward innovative fronts. Furthermore, these visualisations can assist policymakers and healthcare stakeholders in understanding the broader research environment, which is crucial for informed decision-making regarding funding and policy development related to the AMCs’ triple mission.

Suggested Citation

  • Massimo Aria & Corrado Cuccurullo & Luca D’Aniello & Michelangelo Misuraca & Maria Spano, 2024. "Comparative science mapping: a novel conceptual structure analysis with metadata," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 7055-7081, November.
    • Handle: RePEc:spr:scient:v:129:y:2024:i:11:d:10.1007_s11192-024-05161-6
    DOI: 10.1007/s11192-024-05161-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-024-05161-6
    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/s11192-024-05161-6?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. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    2. Corrado Cuccurullo & Massimo Aria & Fabrizia Sarto, 2016. "Foundations and trends in performance management. A twenty-five years bibliometric analysis in business and public administration domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 595-611, August.
    3. M.J. Cobo & A.G. López-Herrera & E. Herrera-Viedma & F. Herrera, 2011. "Science mapping software tools: Review, analysis, and cooperative study among tools," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(7), pages 1382-1402, July.
    4. A. Velez-Estevez & P. García-Sánchez & J. A. Moral-Munoz & M. J. Cobo, 2022. "Why do papers from international collaborations get more citations? A bibliometric analysis of Library and Information Science papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7517-7555, December.
    5. Fabrizio Cesaroni & Andrea Piccaluga, 2016. "The activities of university knowledge transfer offices: towards the third mission in Italy," The Journal of Technology Transfer, Springer, vol. 41(4), pages 753-777, August.
    6. Cobo, M.J. & López-Herrera, A.G. & Herrera-Viedma, E. & Herrera, F., 2011. "An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field," Journal of Informetrics, Elsevier, vol. 5(1), pages 146-166.
    7. van Eck, N.J.P. & Waltman, L., 2009. "How to Normalize Co-Occurrence Data? An Analysis of Some Well-Known Similarity Measures," ERIM Report Series Research in Management ERS-2009-001-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    8. E. C. M. Noyons & H. F. Moed & A. F. J. Raan, 1999. "Integrating research performance analysis and science mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 46(3), pages 591-604, November.
    9. Giovanni Abramo & Andrea D'Angelo, 2009. "The alignment of public research supply and industry demand for effective technology transfer: the case of Italy," Science and Public Policy, Oxford University Press, vol. 36(1), pages 2-14, February.
    10. Ismael Rafols & Alan L. Porter & Loet Leydesdorff, 2010. "Science overlay maps: A new tool for research policy and library management," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(9), pages 1871-1887, September.
    11. M.J. Cobo & A.G. López‐Herrera & E. Herrera‐Viedma & F. Herrera, 2011. "Science mapping software tools: Review, analysis, and cooperative study among tools," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(7), pages 1382-1402, July.
    12. Christian Sternitzke & Isumo Bergmann, 2009. "Similarity measures for document mapping: A comparative study on the level of an individual scientist," Scientometrics, Springer;Akadémiai Kiadó, vol. 78(1), pages 113-130, January.
    13. Healey, Peter & Rothman, Harry & Hoch, Paul K., 1986. "An experiment in science mapping for research planning," Research Policy, Elsevier, vol. 15(5), pages 233-251, October.
    14. Neal Coulter & Ira Monarch & Suresh Konda, 1998. "Software engineering as seen through its research literature: A study in co‐word analysis," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 49(13), pages 1206-1223.
    15. Massimo Aria & Corrado Cuccurullo & Luca D’Aniello & Michelangelo Misuraca & Maria Spano, 2022. "Thematic Analysis as a New Culturomic Tool: The Social Media Coverage on COVID-19 Pandemic in Italy," Sustainability, MDPI, vol. 14(6), pages 1-22, March.
    16. Derya Akcan & Susanna Axelsson & Christina Bergh & Thomas Davidson & Måns Rosén, 2013. "Methodological quality in clinical trials and bibliometric indicators: no evidence of correlations," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 297-303, July.
    17. Massimo Aria & Michelangelo Misuraca & Maria Spano, 2020. "Mapping the Evolution of Social Research and Data Science on 30 Years of Social Indicators Research," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 149(3), pages 803-831, June.
    18. van Eck, N.J.P. & Waltman, L., 2007. "Bibliometric Mapping of the Computational Intelligence Field," ERIM Report Series Research in Management ERS-2007-027-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    19. Dangzhi Zhao, 2010. "Characteristics and impact of grant-funded research: a case study of the library and information science field," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 293-306, August.
    20. Loet Leydesdorff & Henry Etzkowitz, 1998. "The Triple Helix as a model for innovation studies," Science and Public Policy, Oxford University Press, vol. 25(3), pages 195-203, June.
    21. Arho Suominen & Hannes Toivanen, 2016. "Map of science with topic modeling: Comparison of unsupervised learning and human-assigned subject classification," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(10), pages 2464-2476, October.
    22. Tomas Cahlik, 2000. "Search for Fundamental Articles in Economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 49(3), pages 389-402, November.
    23. Zhong-Yi Wang & Gang Li & Chun-Ya Li & Ang Li, 2012. "Research on the semantic-based co-word analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(3), pages 855-875, March.
    24. Sotaro Shibayama & Deyun Yin & Kuniko Matsumoto, 2021. "Measuring novelty in science with word embedding," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-16, July.
    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. Massimo Aria & Luca D’Aniello & Maria Gabriella Grassia & Marina Marino & Rocco Mazza & Agostino Stavolo, 2024. "Mapping the evolution of gender dysphoria research: a comprehensive bibliometric study," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(6), pages 5351-5375, December.
    2. E. M. Murgado-Armenteros & M. Gutiérrez-Salcedo & F. J. Torres-Ruiz & M. J. Cobo, 2015. "Analysing the conceptual evolution of qualitative marketing research through science mapping analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 519-557, January.
    3. Massimo Aria & Michelangelo Misuraca & Maria Spano, 2020. "Mapping the Evolution of Social Research and Data Science on 30 Years of Social Indicators Research," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 149(3), pages 803-831, June.
    4. Ruben Heradio & David Fernandez-Amoros & Cristina Cerrada & Manuel J. Cobo, 2020. "Group Decision-Making Based on Artificial Intelligence: A Bibliometric Analysis," Mathematics, MDPI, vol. 8(9), pages 1-20, September.
    5. Cristina Mele & Jaqueline Pels & Maria Spano & Irene Bernardo, 2023. "Emergent understandings of the market," Italian Journal of Marketing, Springer, vol. 2023(1), pages 1-25, March.
    6. Zamani, Mehdi & Yalcin, Haydar & Naeini, Ali Bonyadi & Zeba, Gordana & Daim, Tugrul U, 2022. "Developing metrics for emerging technologies: identification and assessment," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    7. Rocco Mazza & Roberta Pace & Anna Paterno, 2023. "Themes and policies on population ageing: a bibliometric approach," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 77(2), pages 33-43, April-Jun.
    8. Büşra Ayan & Elif Güner & Semen Son-Turan, 2022. "Blockchain Technology and Sustainability in Supply Chains and a Closer Look at Different Industries: A Mixed Method Approach," Logistics, MDPI, vol. 6(4), pages 1-39, December.
    9. Nguyen, Minh-Hoang & Huyen, Nguyen Thanh Thanh & Pham, Thanh-Hang & Yen, Nguyen Thi Quynh & Vuong, Quan-Hoang, 2020. "On the 50-year research landscape of entrepreneurial finance: A sign of Western ideological homogeneity?," OSF Preprints qf62s, Center for Open Science.
    10. Syed Asif Raza & Rafi Ashrafi & Ali Akgunduz, 2020. "A bibliometric analysis of revenue management in airline industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(6), pages 436-465, December.
    11. Camilla Salvatore, 2023. "Inference with non-probability samples and survey data integration: a science mapping study," METRON, Springer;Sapienza Università di Roma, vol. 81(1), pages 83-107, April.
    12. Cobo, M.J. & López-Herrera, A.G. & Herrera-Viedma, E. & Herrera, F., 2011. "An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field," Journal of Informetrics, Elsevier, vol. 5(1), pages 146-166.
    13. Francesco Foglia, 2023. "Is smart specialisation monopolising the research on the EU cohesion policy? Evidence from a bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(2), pages 1001-1021, February.
    14. Serhat Burmaoglu & Ozcan Saritas, 2019. "An evolutionary analysis of the innovation policy domain: Is there a paradigm shift?," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 823-847, March.
    15. Santana, Monica & Cobo, Manuel J., 2020. "What is the future of work? A science mapping analysis," European Management Journal, Elsevier, vol. 38(6), pages 846-862.
    16. A. Velez-Estevez & P. García-Sánchez & J. A. Moral-Munoz & M. J. Cobo, 2022. "Why do papers from international collaborations get more citations? A bibliometric analysis of Library and Information Science papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7517-7555, December.
    17. Paúl Carrión-Mero & Néstor Montalván-Burbano & Fernando Morante-Carballo & Adolfo Quesada-Román & Boris Apolo-Masache, 2021. "Worldwide Research Trends in Landslide Science," IJERPH, MDPI, vol. 18(18), pages 1-24, September.
    18. Hana Tomaskova & Martin Kopecky, 2020. "Specialization of Business Process Model and Notation Applications in Medicine—A Review," Data, MDPI, vol. 5(4), pages 1-42, October.
    19. Belfiore, Alessandra & Cuccurullo, Corrado & Aria, Massimo, 2022. "IoT in healthcare: A scientometric analysis," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    20. Juntao Zheng & Niancai Liu, 2015. "Mapping of important international academic awards," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 763-791, September.

    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:129:y:2024:i:11:d:10.1007_s11192-024-05161-6. 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.