Global trends in coronavirus research at the time of Covid-19a general bibliometric approach and content analysis using SciMAT

  1. Enrique Herrera-Viedma 1
  2. José-Ricardo López-Robles 2
  3. Javier Guallar 3
  4. Manuel-Jesús Cobo 4
  1. 1 Universidad de Granada
    info

    Universidad de Granada

    Granada, España

    ROR https://ror.org/04njjy449

  2. 2 Universidad Autónoma de Zacatecas
    info

    Universidad Autónoma de Zacatecas

    Zacatecas, México

    ROR https://ror.org/01m296r74

  3. 3 Universitat de Barcelona
    info

    Universitat de Barcelona

    Barcelona, España

    ROR https://ror.org/021018s57

  4. 4 Universidad de Cádiz
    info

    Universidad de Cádiz

    Cádiz, España

    ROR https://ror.org/04mxxkb11

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Revista:
El profesional de la información

ISSN: 1386-6710,  1699-2407

Año de publicación: 2020

Título del ejemplar: Relaciones públicas

Volumen: 29

Número: 3

Tipo: Artículo

DOI: 10.3145/EPI.2020.MAY.22 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: El profesional de la información

Resumen

Covid-19 represents the greatest challenge facing mankind today. In December 2019, several cases of pneumonia of unknown etiology were reported from China. This coronavirus infection subsequently identified as Covid-19 aroused worldwide concern. As a result, the scientific community has focused attention on Covid-19, as revealed by recent research reported in literature based on a holistic approach. In this regard, this study conducts a bibliometric analysis of coronavirus research in the literature with an emphasis on Covid-19 disease, using as a reference the publications in the Web of Science Core Collection from 1970 to 2020. This research analyzes 12,571 publications from 1970 to (April 18) 2020 by applying advanced bibliometric techniques in SciMAT bibliometric analysis software. The current research therefore provides a complete conceptual analysis of the main coronavirus types and strains in the literature by quantifying the main bibliometric performance indicators, identifying the main authors, organizations, countries, sources, and research areas, and evaluating the development of this field. Furthermore, a science map is constructed to understand the corresponding intellectual structure and main research lines (themes). SciMAT thereby offers a complete approach to the field and evaluates the main performance indicators related to coronavirus, with a focus on Covid-19. Finally, this research serves as a framework to strengthen existing research lines and develop new ones, establishing synergistic relationships that were not visible without the maps generated herein.

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Información de financiación

This study has been carried out with support from the “Culture and Digital Content” consolidated research group (SGR 2017-422), funded by the Agency for the Management of University and Research Grants (Agaur) of the Generalitat de Catalunya. Additionally, the authors want to thank the Feder funds (TIN2016-75850-R), Mexican Consejo Nacional de Ciencia y Tecnología (Conacyt), and Mexican Dirección General de Relaciones Internacionales(DGRI) for support.

Financiadores

Referencias bibliográficas

  • Bonilla-Aldana, D. Katterine; Quintero-Rada, Keidenis; Montoya-Posada, Juan Pablo; Ramírez-Ocampo, Sebastián; Paniz-Mondolfi, Alberto; Rabaan, Ali A.; Sah, Ranjit; Rodríguez-Morales, Alfonso J. (2020). “SARS-CoV, MERS-CoV and now the 2019-novel CoV: Have we investigated enough about coronaviruses?–A bibliometric analysis”. Travel medicine and infectious disease, v. 33, 101566. https://doi.org/10.1016/j.tmaid.2020.101566
  • Callon, Michael; Courtial, Jean-Pierre; Turner, William A.; Bauin, Serge (1983). “From translations to problematic networks: An introduction to co-word analysis”. Information (International Social Science Council), v. 22, n. 2, pp. 191-235. https://doi.org/10.1177/053901883022002003
  • Callon, Michael; Courtial, Jean Pierre; Laville, Francoise (1991). “Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemsitry”. Scientometrics, v. 22, n. 1, pp. 155-205. https://doi.org/10.1007/BF02019280
  • Casero-Ripollés, Andreu (2020). “Impact of Covid-19 on the media system. Communicative and democratic consequences of news consumption during the outbreak”. El profesional de la información, v. 29, n. 2, e290223. https://doi.org/10.3145/epi.2020.mar.23
  • Cobo, Manuel-Jesús; López-Herrera, Antonio-Gabriel; Herrera-Viedma, Enrique; Herrera, Francisco (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, v. 5, n. 1, pp. 146-166. https://doi.org/10.1016/j.joi.2010.10.002
  • Cobo, Manuel-Jesús; López-Herrera, Antonio-Gabriel; Herrera-Viedma, Enrique; Herrera, Francisco (2012). “SciMAT: A new science mapping analysis software tool”. Journal of the American Society for Information Science and Technology, v. 63, n. 8, pp. 1609-1630. https://doi.org/10.1002/asi.22688
  • Coulter, Neal; Monarch, Ira; Konda, Suresh (1998). “Software engineering as seen through its research literature: A study in co‐word analysis”. Journal of the American Society for Information Science, v. 49, n. 13, pp. 1206-1223. https://doi.org/10.1002/(SICI)1097-4571(1998)49:13%3C1206::AID-ASI7%3E3.0.CO;2-F
  • Garfield, Eugene (1986). “Towards Scientography”. Current comments, n. 43, pp. 324-335. http://www.garfield.library.upenn.edu/essays/v9p324y1986.pdf
  • Garfield, Eugene; Merton, Robert K. (1979). “Citation indexing: Its theory and application in science, technology, and humanities”. New York: Wiley. ISBN: 978 0 471025597
  • He, Qin (1999). “Knowledge discovery through co-word analysis”. Library trends, v. 48, n. 1, pp. 133-159. https://www.ideals.illinois.edu/bitstream/handle/2142/8267/librarytrendsv48i1i_opt.pdf
  • Hirsch, Jorge E. (2005). “An index to quantify an individual’s scientific research output”. Proceedings of the National academy of Sciences, v. 102, n. 46, pp. 16569-16572. https://doi.org/10.1073/pnas.0507655102
  • Hossain, Md-Mahbub (2020). “Current status of global research on novel coronavirus disease (Covid-19): A bibliometric analysis and knowledge mapping”. F1000 Research. https://doi.org/10.2139/ssrn.3547824
  • Lázaro-Rodríguez, Pedro; Herrera-Viedma, Enrique (2020). “Noticias sobre Covid-19 y 2019-nCoV en medios de comunicación de España: el papel de los medios digitales en tiempos de confinamiento”. El profesional de la información, v. 29, n. 3, e290302. https://doi.org/10.3145/epi.2020.may.02
  • López-Robles, José-Ricardo; Guallar, Javier; Otegi-Olaso, José-Ramón; Gamboa-Rosales, Nadia-Karina (2019a). “El profesional de la información (EPI): bibliometric and thematic analysis (2006-2017)”. El profesional de la información, v. 28, n. 4, e280417. https://doi.org/10.3145/epi.2019.jul.17
  • López-Robles, José-Ricardo; Otegi-Olaso, Jose-Ramón; Porto-Gómez, Igone; Cobo, Manuel-Jesús (2019b). “30 years of intelligence models in management and business: A bibliometric review”. International journal of information management, v. 48, pp. 22-38. https://doi.org/10.1016/j.ijinfomgt.2019.01.013
  • López-Robles, José-Ricardo; Otegi-Olaso, José-Ramón; Porto-Gómez, Igone; Gamboa-Rosales, Hamurabi; Gamboa-Rosales, Nadia-Karina (2020). “Understanding the intellectual structure and evolution of competitive intelligence: A bibliometric analysis from 1984 to 2017”. Technology analysis & strategic management, v. 32, n. 5, pp. 604-619. https://doi.org/10.1080/09537325.2019.1686136
  • Martínez, Miguel-Ángel; Cobo, Manuel-Jesús; Herrera, Manuel; Herrera-Viedma, Enrique (2015). “Analyzing the scientific evolution of social work using science mapping”. Research on social work practice, v. 25, n. 2, pp. 257-277. https://doi.org/10.1177/1049731514522101
  • Martínez, Miguel-Ángel; Herrera, Manuel; López-Gijón, Javier; Herrera-Viedma, Enrique (2014). “H-Classics: Characterizing the concept of citation classics through H-index”. Scientometrics, v. 98, n. 3, pp. 1971-1983. https://doi.org/10.1007/s11192-013-1155-9
  • Moed, Henk F. (2009). “New developments in the use of citation analysis in research evaluation”. Archivum immunologiae et therapiae experimentalis, v. 57, 13. https://doi.org/10.1007/s00005-009-0001-5
  • Moed, Henk F.; De-Bruin, R. E.; Van-Leeuwen, Thed (1995). “New bibliometric tools for the assessment of national research performance: Database description, overview of indicators and first applications”. Scientometrics, v. 33, n. 3, pp. 381-422. https://doi.org/10.1007/BF02017338
  • Moral-Muñoz, José A; Herrera-Viedma, Enrique; Santisteban-Espejo, Antonio; Cobo, Manuel-Jesús (2020). “Software tools for conducting bibliometric analysis in science: An up-to-date review”. El profesional de la información v. 29, n. 1, e290103. https://doi.org/10.3145/epi.2020.ene.03
  • Pérez-Dasilva, Jesús-Ángel; Meso-Ayerdi, Koldobika; Mendiguren-Galdospín, Terese (2020). “Fake news y coronavirus: detección de los principales actores y tendencias a través del análisis de las conversaciones en Twitter”. El profesional de la información, v. 29, n. 3, e290308. https://doi.org/10.3145/epi.2020.may.08
  • Rodríguez-Morales, Alfonso J.; Cardona-Ospina, Jaime A.; Gutiérrez-Ocampo, Estefanía; Villamizar-Peña, Rhuvi; Holguin-Rivera, Yeimer; Escalera-Antezana, Juan-Pablo; Alvarado-Arnez, Lucia-Elena; Bonilla-Aldana, D. Katterine; Franco-Paredes, Carlos; Henao-Martínez, Andrés F. (2020). “Clinical, laboratory and imaging features of Covid-19: A systematic review and meta-analysis”. Travel medicine and infectious disease, v. 34, 101623. https://doi.org/10.1016/j.tmaid.2020.101623
  • Sahin, Ahmet-Riza; Erdogan, Aysegul; Agaoglu, Pelin-Mutlu; Dineri, Yeliz; Cakirci, Ahmet-Yusuf; Senel, Mahmut-Egemen; Okyay, Ramazan-Azim; Tasdogan, Ali-Muhittin (2020). “2019 novel coronavirus (Covid-19) outbreak: a review of the current literature”. EJMO, v. 4, n. 1, pp. 1-7. https://dx.doi.org/10.14744/ejmo.2020.12220
  • Thelwall, Mike; Thelwall, Saheeda (2020). “Covid-19 tweeting in English: Gender differences”. El profesional de la información, v. 29, n. 3, e290301. https://doi.org/10.3145/epi.2020.may.01
  • Torres-Salinas, Daniel (2020). “Ritmo de crecimiento diario de la producción científica sobre Covid-19. Análisis en bases de datos y repositorios en acceso abierto”. El profesional de la información, v. 29, n. 2, e290215. https://doi.org/10.3145/epi.2020.mar.15
  • Wang, Jian (2013). “Citation time window choice for research impact evaluation”. Scientometrics, v. 94, n. 3, pp. 851-872. https://doi.org/10.1007/s11192-012-0775-9
  • WHO (2020). “Coronavirus disease 2019 (Covid-19)”. WHO Situation report. World Health Organization, n. 72. https://apps.who.int/iris/bitstream/handle/10665/331685/nCoVsitrep01Apr2020-eng.pdf
Fuente de los datos: Dialnet