Aleksander Aristovnik (Author), Dejan Ravšelj (Author), Lan Umek (Author)

Abstract

The lack of knowledge about the COVID-19 pandemic has encouraged extensive research in the academic sphere, reflected in the exponentially growing scientific literature. While the state of COVID-19 research reveals it is currently in an early stage of developing knowledge, a comprehensive and in-depth overview is still missing. Accordingly, the paper’s main aim is to provide an extensive bibliometric analysis of COVID-19 research across the science and social science research landscape, using innovative bibliometric approaches (e.g., Venn diagram, Biblioshiny descriptive statistics, VOSviewer co-occurrence network analysis, Jaccard distance cluster analysis, text mining based on binary logistic regression). The bibliometric analysis considers the Scopus database, including all relevant information on COVID-19 related publications (n = 16,866) available in the first half of 2020. The empirical results indicate the domination of health sciences in terms of number of relevant publications and total citations, while physical sciences and social sciences and humanities lag behind significantly. Nevertheless, there is an evidence of COVID-19 research collaboration within and between different subject area classifications with a gradual increase in importance of non-health scientific disciplines. The findings emphasize the great need for a comprehensive and in-depth approach that considers various scientific disciplines in COVID-19 research so as to benefit not only the scientific community but evidence-based policymaking as part of efforts to properly respond to the COVID-19 pandemic.

Keywords

COVID-19;coronavirus;pandemic;science;social science;bibliometric analysis;Jaccard distance;text mining;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UL FU - Faculty of Administration
UDC: 3:004
COBISS: 35473155 Link will open in a new window
ISSN: 2071-1050
Views: 158
Downloads: 97
Average score: 0 (0 votes)
Metadata: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Other data

Secondary language: Slovenian
Secondary keywords: COVID-19;koronavirus;pandemija;znanost;družbene vede;bibliometrična analiza;Jaccardova razdalja;tekstovno rudarjenje;
Type (COBISS): Article
Pages: str. 1-30
Volume: ǂVol. ǂ12
Issue: ǂiss. ǂ21
Chronology: 2020
DOI: 10.3390/su12219132
ID: 14294132