medigraphic.com
ISSN 2307-2113 (Electronic)
Revista Cubana de Información en Ciencias de la Salud (ACIMED)

2021, Number 3

<< Back Next >>

Revista Cubana de Información en Ciencias de la Salud (ACIMED) 2021; 32 (3)

Intellectual structure of scientific production on COVID-19 in the area of Public, Environmental and Occupational Health

Limaymanta CH, Amado J, Suclupe-Navarro P, Restrepo-Arango C

Language: Spanish
References: 27
Page: 1-20
PDF size: 903.43 Kb.


ABSTRACT

The aim was to identify the intellectual structure of the scientific production on COVID-19 in the area of Public, Environmental and Occupational Health. Author bibliographic-coupling analysis and author cocitation analysis were used from the scientific production in Web of Science Core Collection in the period December 2019 to August 2020. The units of analysis were the citing authors and cited authors. A total of 1065 records were retrieved under the established search criteria. The Author bibliographic-coupling analysis identified 12 clusters representing 106 major active authors who investigated the pandemic from different perspectives forming diverse research fronts. The author cocitation analysis obtained 96 most influential cited authors represented in five clusters. The WHO and CDC-USA were identified as very influential references, as well as authors from the People's Republic of China. In conclusion, it was possible to identify the intellectual structure of scientific production on COVID-19 in the area of Public, Environmental and Occupational Health with the use of bibliometric methods of author bibliographic-coupling and author cocitation analysis.


REFERENCES

  1. Yang Y, Xiao Z, Ye K, He X, Sun B, Qin Z, et al. SARS-CoV-2: characteristics and current advances in research. Virol J. 2020;17(1):117. DOI: https://doi.org/10.1186/s12985-020-01369-z

  2. Johns Hopkins University. COVID-19 Dashboard by the Center for Systems Science and Engineering. Johns Hopkins University Website; 2020 [acceso: 19/08/2020]. Disponible en: Disponible en: https://coronavirus.jhu.edu/map.html

  3. Romano CM, Chebabo A, Levi JE. Past, present, and future of COVID-19: a review. Braz J Med Biol Res. 2020;53(9):1-8. DOI: https://doi.org/10.1590/1414-431x202010475

  4. Nabil A, Uto K, Elshemy MM, Soliman R, Hassan AA, Ebara M, et al. Current coronavirus (SARS-CoV-2) epidemiological, diagnostic and therapeutic approaches: An updated review until June 2020. EXCLI J. 2020;19:992-1016. DOI: https://doi.org/10.17179/excli2020-2554

  5. Acosta G, Escobar G, Bernaola G, Alfaro J, Taype W, Marcos C, et al. Caracterización de pacientes con COVID-19 grave atendidos en un hospital de referencia nacional del Perú. Rev Per Med Exp Salud Públ. 2020;37(2):253-8. DOI: https://doi.org/10.17843/rpmesp.2020.372.5437

  6. Zhao D, Strotmann A. Evolution of research activities and intellectual influences in information science 1996-2005: Introducing author bibliographic-coupling analysis. J Am Soc Inf Sci Technol. 2008;59(13):2070-86. DOI: https://doi.org/10.1002/asi.20910

  7. White HD, Griffith BC. Author cocitation: A literature measure of intellectual structure. J Am Soc Inf Sci. 1981;32(3):163-71. DOI: https://doi.org/10.1002/asi.4630320302

  8. González-Alcaide G, Calafat A, Becoña E. Núcleos y ámbitos de investigación sobre adicciones en España a través del análisis de los enlaces bibliográficos en la Web of Science (2000-2013). Adicciones. 2014;26(2):168-83. DOI: https://doi.org/10.20882/adicciones.20

  9. Kessler MM. Bibliographic coupling between scientific papers. Am Doc. 1963;14(1):10-25. DOI: https://doi.org/10.1002/asi.5090140103

  10. Small H. Co-citation in the scientific literature: A new measure of the relationship between two documents. J Am Soc Inf Sci. 1973;24(4):265-9. DOI: https://doi.org/10.1002/asi.4630240406

  11. Marshakova-Shaikevich I. System of Document Connections Based on References. Naunchn-Techn Inform. 1973 [acceso: 02/09/2020];2(6):3-8. Disponible en: Disponible en: http://garfield.library.upenn.edu/marshakova/marshakovanauchtechn1973.pdf

  12. Miguel S, Moya-Anegón F, Herrero-Solana V. El análisis de co-citas como método de investigación en Bibliotecología y Ciencia de la Información. Investig Bibl Arch Bibliotecol E Inf. 2007;21(43). DOI: https://doi.org/10.22201/iibi.0187358xp.2007.43.4129

  13. White HD, McCain KW. Visualizing a discipline: An author co-citation analysis of information science, 1972-1995. J Am Soc Inf Sci. 1998;49(4):327-55. DOI: https://doi.org/10.1002/(SICI)1097-4571(19980401)49:4<327:AID-ASI4>3.0.CO;2-4

  14. Vargas-Quesada B, de Moya-Anegón F. Visualizing the structure of science. Berlin, Heidelberg: Springer; 2007. p. 235-40. DOI: https://doi.org/10.1007/3-540-69728-4_8

  15. Lou J, Tian S, Niu S, Kang X, Lian H, Zhang L, et al. Coronavirus disease 2019: a bibliometric analysis and review. Eur Rev Med Pharmacol Sci. 2020;24(6):3411-21. DOI: https://doi.org/10.26355/eurrev_202003_20712

  16. Haghani M, Bliemer MCJ, Goerlandt F, Li J. The scientific literature on Coronaviruses, COVID-19 and its associated safety-related research dimensions: A scientometric analysis and scoping review. Saf Sci. 2020;129:104806. DOI: https://doi.org/10.1016/j.ssci.2020.104806

  17. Gregorio-Chaviano O, Limaymanta CH, López-Mesa EK. Análisis bibliométrico de la producción científica latinoamericana sobre COVID-19. Biomédica. 2020;40(Supl. 2). DOI: https://doi.org/10.7705/biomedica.5571

  18. Hamidah I, Sriyono S, Hudha MN. A Bibliometric Analysis of Covid-19 Research using VOSviewer. Indones J Sci Technol. 2020;5(2):209-16. DOI: https://doi.org/10.17509/ijost.v5i2.24522

  19. Ortiz-Núñez R. Análisis métrico de la producción científica sobre COVID-19 en SCOPUS. Rev Cubana Inf Cienc Salud. 2020;31(3). DOI: https://doi.org/10.36512/rcics.v31i2.1587

  20. Cornelius B, Landström H, Persson O. Entrepreneurial Studies: The Dynamic Research Front of a Developing Social Science: Entrep Theory Pract. 2017;30(3):375-98. DOI: https://doi.org/10.1111/j.1540-6520.2006.00125.x

  21. Zhao D, Strotmann A. The knowledge base and research front of information science 2006-2010: An author cocitation and bibliographic coupling analysis. J Assoc Inf Sci Technol. 2014;65(5):995-1006. DOI: https://doi.org/10.1002/asi.23027

  22. van Eck NJ, Waltman L. VOSviewer Manual. Leiden University; 2017[acceso: 19/08/2020]. Disponible en: Disponible en: https://www.vosviewer.com/getting-started

  23. van Eck NJ, Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics. 2010;84(2):523-38. DOI: https://doi.org/10.1007/s11192-009-0146-3

  24. van Eck NJ, Waltman L. Visualizing Bibliometric Networks. En: Ding Y, Rousseau R, Wolfram D, editores. Measuring Scholarly Impact. Spring Internat Publ; 2014. p. 285-320. DOI: https://doi.org/10.1007/978-3-319-10377-8_13

  25. van Eck NJ, Waltman L. How to normalize cooccurrence data? An analysis of some well-known similarity measures. J Am Soc Inf Sci Technol. 2009;60(8):1635-51. DOI: https://doi.org/10.1002/asi.21075

  26. Waltman L, van Eck NJ, Noyons ECM. A unified approach to mapping and clustering of bibliometric networks. J Informetr. 2010;4(4):629-35. DOI: https://doi.org/10.1016/j.joi.2010.07.002

  27. Aleixandre-Benavent R, Castelló-Cogollos L, Valderrama-Zurián JC. Información y comunicación durante los primeros meses de Covid-19. Infodemia, desinformación y papel de los profesionales de la información. EPI. 2020;29(4):e290408. DOI: https://doi.org/10.3145/epi.2020.jul.08




2020     |     www.medigraphic.com