Exploring Visitor Sentiment Trends at Alanya Cleopatra Beach Using Natural Language Processing Techniques: Insights from Online Reviews
Abstract
Purpose
This
study
aims
to
analyze
online
reviews
of
Cleopatra
Beach,
utilizing
Natural
Language
Processing
(NLP)
techniques
uncover
key
visitor
satisfaction
drivers
and
areas
requiring
management
improvement.
Design/methodology/approach
A
dataset
5,238
from
TripAdvisor
(2008–2024)
was
analyzed
using
NLP
such
as
sentiment
analysis
topic
modeling.
Linear
regression
applied
predict
trends
for
2025–2030,
providing
insights
into
future
levels.
Findings
Positive
themes,
natural
beauty,
relaxation,
amenities,
dominated
the
reviews,
while
cleanliness,
safety,
overcrowding
emerged
significant
negative
themes.
Sentiment
highlighted
an
overall
dominance
positive
feedback,
though
saw
a
notable
increase
post-2020,
potentially
linked
pandemic-related
challenges.
Future
predictions
suggest
strategic
improvements
in
crowd
enhance
satisfaction.
Originality/value
By
integrating
methods,
this
research
showcases
potential
feedback
destination
management.
The
findings
contribute
sustainable
tourism
strategies
exemplify
role
enhancing
operational
efficiency.
Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 22, 2025
Language: Английский