Abstract
A world crisis brings forth new, often unexpected responses that are fascinating to investigate from both scientific and social standpoints. A comprehensive bibliometric investigation of such an event can offer insights into politics of the pandemic, not just providing incentives for improving scientific quality and productivity, but also dissecting the role of global competition and marginalization in terms of funding and peerage. The sheer numbers of publications witnessed in less than 10 months of the novel coronavirus outbreak, indicates how scientists from all walks of life, irrespective of their respective fields of interests, shifted to COVID19 research, leading to discoveries and new directions of research for many. However, this shift has also resulted in shocking factoids based on incomplete interpretations of scientific data, which have continued to be foisted on the public at an alarming rate during the past nine months of COVID, the most colossal of these being the Lancet HCQ story. In this work, we use the 2020 COVID-19 publications to identify bibliometric communities that we compare temporally across two major epidemics of SARS and MERS.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aria, M., Cuccurullo, C.: bibliometrix: an R-tool for comprehensive science mapping analysis. J. Informetr. 11(4), 959–975 (2017). https://doi.org/10.1016/j.joi.2017.08.007
Aria, M., Misuraca, M., Spano, M.: Mapping the evolution of social research and data science on 30 years of social indicators research. Soc. Indicator. Res. 1–29 (2020). https://doi.org/10.1007/s11205-020-02281-3
Babu, S., Yadav, G.: NEXCADE: a method for perturbation of complex Networks. PloS ONE (2012)
Cuccurullo, C., Aria, M., Sarto, F.: Twenty years of research on performance management in business and public administration domains. In: Academy of Management Proceedings, vol. 2013, no. 1, p. 14270. Academy of Management (2013)
Jiménez, A., Bjorvatn, T.: The building blocks of political risk research: a bibliometric co-citation analysis. Int. J. Emerg. Mark. (2018)
Mishra, P., Prasad, A., Babu, S., Yadav, G.: Bibliometric Networks for Research: Decision Support Systems based on Scientific Evidence (2020)
Mali, F., Kronegger, L., Doreian, P., Ferligoj, A.: Dynamic scientific co-authorship networks. In: Models of Science Dynamics, 2012, pp. 195–232. https://doi.org/10.1007/978-3-642-23068-4_6
Newman, M.E.: Coauthorship networks and patterns of scientific collaboration. Proc. Natl. Acad. Sci. 101(Suppl 1), 5200–5205 (2004). https://doi.org/10.1073/pnas.0307545100
Shannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., Amin, N., Schwikowski, B., Ideker, T.: Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13 2498–2504 (2003)
Skippari, M., Eloranta, J., Lamberg, J., Parviainen, P.: Conceptual and theoretical underpinnings in the research of corporate political activity: a bibliometric analysis. Liiketaloudellinen aikakauskirja 2, 185 (2005)
Ziman, J.: Are debatable scientific questions debatable? Soc. Epistemol. 14(2–3), 187–199 (2000). https://doi.org/10.1080/02691720050199225
Acknowledgements
RG and AP acknowledge CSIR Junior Research Fellowship. GY acknowledges CSIR Grant ID 38(1461)/18/EMR-II and RCUK-BBSRC Grant ID BBSRC BB/P027970/1TIGR2ESS, as well as NIPGR support. SB acknowledges support from School of Human Ecology, AUD.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Gupta, R., Prasad, A., Babu, S., Yadav, G. (2021). Temporal Bibliometry Networks of SARS, MERS and COVID19 Reveal Dynamics of the Pandemic. In: Benito, R.M., Cherifi, C., Cherifi, H., Moro, E., Rocha, L.M., Sales-Pardo, M. (eds) Complex Networks & Their Applications IX. COMPLEX NETWORKS 2020 2020. Studies in Computational Intelligence, vol 944. Springer, Cham. https://doi.org/10.1007/978-3-030-65351-4_56
Download citation
DOI: https://doi.org/10.1007/978-3-030-65351-4_56
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-65350-7
Online ISBN: 978-3-030-65351-4
eBook Packages: EngineeringEngineering (R0)