PyBibX – a Python library for bibliometric and scientometric analysis powered with artificial intelligence tools
Data Technologies and Applications,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 27, 2025
Purpose
This
paper
presents
pyBibX,
a
Python
library
devised
to
conduct
comprehensive
bibliometric
and
scientometric
analyses
on
raw
data
files
sourced
from
Scopus,
Web
of
Science
PubMed,
seamlessly
integrating
state-of-the-art
artificial
intelligence
(AI)
capabilities
into
its
core
functionality.
Design/methodology/approach
The
executes
exploratory
analysis
(EDA),
presenting
outcomes
via
visually
appealing
graphical
illustrations.
Network
have
been
deftly
integrated,
encompassing
citation,
collaboration
similarity
analysis.
Furthermore,
the
incorporates
AI
capabilities,
including
embedding
vectors,
topic
modeling,
text
summarization
other
general
natural
language
processing
tasks,
employing
models
such
as
sentence-BERT,
BerTopic,
BERT,
chatGPT
PEGASUS.
Findings
As
demonstration,
we
analyzed
184
documents
associated
with
“multiple-criteria
decision
analysis”
published
between
1984
2023.
EDA
emphasized
growing
fascination
decision-making
fuzzy
logic
methodologies.
Next,
network
further
accentuated
significance
central
authors
intra-continental
collaboration,
identifying
Canada
China
crucial
hubs.
Finally,
distinguished
two
primary
topics
chatGPT’s
preeminence
in
summarization.
It
also
proved
be
an
indispensable
instrument
for
interpreting
results,
our
enables
researchers
pose
inquiries
regarding
outcomes.
Even
so,
homogeneity
remains
daunting
challenge
due
database
inconsistencies.
Originality/value
PyBibX
is
first
application
cutting-edge
analyzing
scientific
publications,
enabling
examine
interpret
these
more
effectively.
pyBibX
freely
available
at
https://bit.ly/442wD5z.
Language: Английский
Comment on ‘Research contribution of bibliometric studies related to sustainable development goals and sustainability’ [Discover Sustainability, 2023, 5, 1, 7, 10.1007/s43621-024-00182-w]
Discover Sustainability,
Journal Year:
2024,
Volume and Issue:
5(1)
Published: July 30, 2024
Abstract
This
investigation
discusses
a
comment
on
recently
published
research
study
(Raman,
Discov
Sustain
5:7,
2024)
related
to
Sustainable
Development
Goals
(SDGs)
and
Sustainability,
focusing
bibliometric
analysis.
The
observation
highlighted
computational
error
in
the
calculation
of
Compound
Annual
Growth
Rate
(CAGR)
as
presented
original
publication.
A
revised
formula
was
provided,
along
with
corrected
computations,
revealing
notable
disparity
growth
forecasts.
It
emphasizes
need
use
appropriate
formulas
for
assessments
suggests
that
researchers
should
focus
identifying
rectifying
inaccuracies.
Language: Английский
An Analysis of Islamic Stock Markets Literature: Trends, Emerging Themes and Future Prospects
Kocatepe İslami İlimler Dergisi,
Journal Year:
2024,
Volume and Issue:
7(3), P. 1 - 24
Published: Dec. 20, 2024
This
study
aims
to
provide
a
comprehensive
overview
of
current
knowledge,
highlight
research
gaps,
and
identify
emerging
trends
guide
future
in
the
area
Islamic
stock
markets.
It
addresses
lack
thorough
bibliometric
analysis
this
using
reliable
databases
such
as
Scopus.
The
applied
on
624
documents
retrieved
from
Scopus
database
certain
criteria.
Bibliometrix
R
package
was
used
perform
analysis.
In
way,
most
prolific
affiliations,
authors,
documents,
scientific
networks
between
different
countries,
co-occurrence
co-citation
networks,
field
were
identified
study.
results
reveal
that
Pacific
Basin
Finance
Journal
International
Middle
Eastern
Management
are
journals
contribute
field.
also
reveals
influential
authors
M.
Masih
S.
Hammoudeh.
Malaysian
universities
productive
institutions,
while
Malaysia
is
cooperative
country
according
cooperation
network.
studied
topics
comparison
conventional
markets
terms
performance
volatility
spillovers
them.
New
within
have
focused
more
COVID-19
bitcoin.
Most
studies
finance
banking,
sukuk,
capital
takaful.
Language: Английский