Your browser does not allow JavaScript!
JavaScript is necessary for the proper functioning of this website. Please enable JavaScript or use a modern browser.
Open Science Slovenia
Open Science
DiKUL
slv
|
eng
Search
Browse
New in RUL
About RUL
In numbers
Help
Sign in
A bibliometric analysis of COVID-19 across science and social science research landscape
ID
Aristovnik, Aleksander
(
Author
),
ID
Ravšelj, Dejan
(
Author
),
ID
Umek, Lan
(
Author
)
PDF - Presentation file,
Download
(4,78 MB)
MD5: A49649C65E5D0A90E43CEBD2F6BB69FE
URL - Source URL, Visit
https://www.mdpi.com/2071-1050/12/21/9132
Image galllery
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.
Language:
English
Keywords:
COVID-19
,
coronavirus
,
pandemic
,
science
,
social science
,
bibliometric analysis
,
Jaccard distance
,
text mining
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
FU - Faculty of Administration
Publication status:
Published
Publication version:
Version of Record
Year:
2020
Number of pages:
30 str.
Numbering:
Vol. 12, iss. 21, art. 9132
PID:
20.500.12556/RUL-134443
UDC:
3:004
ISSN on article:
2071-1050
DOI:
10.3390/su12219132
COBISS.SI-ID:
35473155
Publication date in RUL:
14.01.2022
Views:
850
Downloads:
411
Metadata:
Cite this work
Plain text
BibTeX
EndNote XML
EndNote/Refer
RIS
ABNT
ACM Ref
AMA
APA
Chicago 17th Author-Date
Harvard
IEEE
ISO 690
MLA
Vancouver
:
Copy citation
Share:
Record is a part of a journal
Title:
Sustainability
Shortened title:
Sustainability
Publisher:
MDPI
ISSN:
2071-1050
COBISS.SI-ID:
5324897
Licences
License:
CC BY 4.0, Creative Commons Attribution 4.0 International
Link:
http://creativecommons.org/licenses/by/4.0/
Description:
This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:
03.11.2020
Secondary language
Language:
Slovenian
Keywords:
COVID-19
,
koronavirus
,
pandemija
,
znanost
,
družbene vede
,
bibliometrična analiza
,
Jaccardova razdalja
,
tekstovno rudarjenje
Projects
Funder:
ARRS - Slovenian Research Agency
Project number:
P5-0093
Name:
Razvoj sistema učinkovite in uspešne javne uprave
Similar documents
Similar works from RUL:
Similar works from other Slovenian collections:
Back