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

Povzetek

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.

Ključne besede

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

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UL FU - Fakulteta za upravo
UDK: 3:004
COBISS: 35473155 Povezava se bo odprla v novem oknu
ISSN: 2071-1050
Št. ogledov: 158
Št. prenosov: 97
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Slovenski jezik
Sekundarne ključne besede: COVID-19;koronavirus;pandemija;znanost;družbene vede;bibliometrična analiza;Jaccardova razdalja;tekstovno rudarjenje;
Vrsta dela (COBISS): Članek v reviji
Strani: str. 1-30
Letnik: ǂVol. ǂ12
Zvezek: ǂiss. ǂ21
Čas izdaje: 2020
DOI: 10.3390/su12219132
ID: 14294132