IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v127y2022i3d10.1007_s11192-021-04260-y.html
   My bibliography  Save this article

Discovering temporal scientometric knowledge in COVID-19 scholarly production

Author

Listed:
  • Breno Santana Santos

    (Federal University of Rio Grande do Norte
    Federal University of Sergipe)

  • Ivanovitch Silva

    (Federal University of Rio Grande do Norte)

  • Luciana Lima

    (Federal University of Rio Grande do Norte)

  • Patricia Takako Endo

    (University of Pernambuco)

  • Gisliany Alves

    (Federal University of Rio Grande do Norte)

  • Marcel da Câmara Ribeiro-Dantas

    (Sorbonne Université (EDITE))

Abstract

The mapping and analysis of scientific knowledge makes it possible to identify the dynamics and/or growth of a particular field of research or to support strategic decisions related to different research entities, based on bibliometric and/or scientometric indicators. However, with the exponential growth of scientific production, a systematic and data-oriented approach to the analysis of this large set of productions becomes increasingly essential. Thus, in this work, a data-oriented methodology was proposed, combining Data Analysis, Machine Learning and Complex Network Analysis techniques, and Data Version Control (DVC) tool, for the extraction of implicit knowledge in scientific production bases. In addition, the approach was validated through a case study in a COVID-19 manuscripts dataset, which had 199,895 articles published on arXiv, bioRxiv, medRxiv, PubMed and Scopus databases. The results suggest the feasibility of the proposed methodology, indicating the most active countries and the most explored themes in each period of the pandemic. Therefore, this study has the potential to instrument and expand strategic decisions by the scientific community, aiming at extracting knowledge that supports the fight against the COVID-19 pandemic.

Suggested Citation

  • Breno Santana Santos & Ivanovitch Silva & Luciana Lima & Patricia Takako Endo & Gisliany Alves & Marcel da Câmara Ribeiro-Dantas, 2022. "Discovering temporal scientometric knowledge in COVID-19 scholarly production," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1609-1642, March.
  • Handle: RePEc:spr:scient:v:127:y:2022:i:3:d:10.1007_s11192-021-04260-y
    DOI: 10.1007/s11192-021-04260-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-021-04260-y
    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/s11192-021-04260-y?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. Brown, Malcolm C., 1994. "Using gini-style indices to evaluate the spatial patterns of health practitioners: Theoretical considerations and an application based on Alberta data," Social Science & Medicine, Elsevier, vol. 38(9), pages 1243-1256, May.
    2. Yves Fassin, 2021. "Research on Covid-19: a disruptive phenomenon for bibliometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 5305-5319, June.
    3. Ashkan Ebadi & Pengcheng Xi & Stéphane Tremblay & Bruce Spencer & Raman Pall & Alexander Wong, 2021. "Understanding the temporal evolution of COVID-19 research through machine learning and natural language processing," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 725-739, January.
    4. Milad Haghani & Pegah Varamini, 2021. "Temporal evolution, most influential studies and sleeping beauties of the coronavirus literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 7005-7050, August.
    5. Lin Zhang & Wenjing Zhao & Beibei Sun & Ying Huang & Wolfgang Glänzel, 2020. "How scientific research reacts to international public health emergencies: a global analysis of response patterns," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 747-773, July.
    6. Nicola Di Girolamo & Reint Meursinge Reynders, 2020. "Characteristics of scientific articles on COVID-19 published during the initial 3 months of the pandemic," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 795-812, October.
    7. X. Cai & C. V. Fry & C. S. Wagner, 2021. "International collaboration during the COVID-19 crisis: autumn 2020 developments," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3683-3692, April.
    8. Milad Haghani & Michiel C. J. Bliemer, 2020. "Covid-19 pandemic and the unprecedented mobilisation of scholarly efforts prompted by a health crisis: Scientometric comparisons across SARS, MERS and 2019-nCoV literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2695-2726, December.
    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. Török, Ádám & Konka, Boglárka & Nagy, Andrea Magda, 2023. "A koronavírus-járvány a közgazdasági szakirodalomban. Egy új határterület tudománymetriai elemzése [The coronavirus pandemic in the economics literature. The scientometric analysis of a new discipl," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 284-304.
    2. Yujie Zhang & Hongzhen Li & Jingyi Mao & Guoxiu He & Yunhan Yang & Zhuoren Jiang & Yufeng Duan, 2023. "COVID-19: a disruptive impact on the knowledge support of references," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4791-4823, August.
    3. Constantin Bürgi & Klaus Wohlrabe, 2022. "The influence of Covid-19 on publications in economics: bibliometric evidence from five working paper series," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5175-5189, September.
    4. Milad Haghani & Pegah Varamini, 2021. "Temporal evolution, most influential studies and sleeping beauties of the coronavirus literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 7005-7050, August.
    5. Yves Fassin, 2021. "Research on Covid-19: a disruptive phenomenon for bibliometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 5305-5319, June.
    6. Mona Farouk Ali, 2022. "Between panic and motivation: did the first wave of COVID-19 affect scientific publishing in Mediterranean countries?," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3083-3115, June.
    7. Gabriela F. Nane & Nicolas Robinson-Garcia & François Schalkwyk & Daniel Torres-Salinas, 2023. "COVID-19 and the scientific publishing system: growth, open access and scientific fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 345-362, January.
    8. Mario Coccia, 2021. "Evolution and structure of research fields driven by crises and environmental threats: the COVID-19 research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(12), pages 9405-9429, December.
    9. Danilo Silva Carvalho & Lucas Lopes Felipe & Priscila Costa Albuquerque & Fabio Zicker & Bruna de Paula Fonseca, 2023. "Leadership and international collaboration on COVID-19 research: reducing the North–South divide?," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4689-4705, August.
    10. Jiban K. Pal, 2021. "Visualizing the knowledge outburst in global research on COVID-19," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4173-4193, May.
    11. Zhao, Yi & Liu, Lifan & Zhang, Chengzhi, 2022. "Is coronavirus-related research becoming more interdisciplinary? A perspective of co-occurrence analysis and diversity measure of scientific articles," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    12. Giovanni Abramo & Ciriaco Andrea D’Angelo & Ida Mele, 2022. "Impact of Covid-19 on research output by gender across countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 6811-6826, December.
    13. Rousseau, Ronald & Garcia-Zorita, Carlos & Sanz-Casado, Elías, 2023. "Publications during COVID-19 times: An unexpected overall increase," Journal of Informetrics, Elsevier, vol. 17(4).
    14. Yi Zhang & Xiaojing Cai & Caroline V. Fry & Mengjia Wu & Caroline S. Wagner, 2021. "Topic evolution, disruption and resilience in early COVID-19 research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4225-4253, May.
    15. Rubini, Lauretta & Pollio, Chiara & Barbieri, Elisa & Cattaruzzo, Sebastiano, 2024. "Changing structures in transnational research networks: An analysis of the impact of COVID-19 on China's scientific collaborations," Structural Change and Economic Dynamics, Elsevier, vol. 69(C), pages 281-297.
    16. Shir Aviv-Reuven & Ariel Rosenfeld, 2021. "Publication patterns’ changes due to the COVID-19 pandemic: a longitudinal and short-term scientometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6761-6784, August.
    17. Lalinsky, Tibor & Pál, Rozália, 2022. "Distribution of COVID-19 government support and its consequences for firm liquidity and solvency," Structural Change and Economic Dynamics, Elsevier, vol. 61(C), pages 305-335.
    18. Ignacio Rodríguez-Rodríguez & José-Víctor Rodríguez & Niloofar Shirvanizadeh & Andrés Ortiz & Domingo-Javier Pardo-Quiles, 2021. "Applications of Artificial Intelligence, Machine Learning, Big Data and the Internet of Things to the COVID-19 Pandemic: A Scientometric Review Using Text Mining," IJERPH, MDPI, vol. 18(16), pages 1-29, August.
    19. Kelly Goossens, 2006. "Competitive balance in european football: comparison by adapting measures: national measure of seasonal imbalance and Top 3," Rivista di Diritto ed Economia dello Sport, Centro di diritto e business dello Sport, vol. 2(2), pages 77-122, Dicembre.
    20. Houcemeddine Turki & Mohamed Ali Hadj Taieb & Mohamed Ben Aouicha, 2022. "Awakening sleeping beauties during the COVID-19 pandemic influences the citation impact of their references," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 6047-6050, October.

    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:127:y:2022:i:3:d:10.1007_s11192-021-04260-y. 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.