Acta Psychologica,
Journal Year:
2024,
Volume and Issue:
249, P. 104463 - 104463
Published: Aug. 24, 2024
The
study
investigates
the
impact
of
tourist
behavior
change
on
travel
agencies
in
developing
countries,
with
a
focus
strategies
for
enhancing
experience.
research
aims
to
identify
main
factors
influencing
purchasing
and
understand
their
relationship
customer
Data
were
collected
from
368
experienced
tourists
Ho
Chi
Minh
City
Hanoi,
Vietnam,
using
combination
convenience
random
sampling.
Partial
Least
Squares
Structural
Equation
modeling
(PLS-SEM)
is
employed
analyze
model.
findings
confirm
that
product
quality,
price,
brand
image,
marketing
strategy
significantly
influence
behavior.
Importantly,
results
highlight
indirect
effect
these
behavior,
mediated
through
It
suggests
experience
crucial
aspect
decisions.
Based
findings,
industry
managers
agents
countries
should
prioritize
building
strong
personalized
services,
digital
integration,
active
social
media
engagement.
Implementing
dynamic
pricing
targeted
campaigns
address
safety
concerns
local
experiences
are
competitiveness
attracting
travelers
post-crisis.
Future
explore
long-term
effects
agency
performance
adapt
model
specific
regional
contexts.
By
adopting
multifaceted
approaches,
can
enhance
better
navigate
changing
post-crisis
era.
Natural
language
processing
(NLP)
is
a
developing
vicinity
of
studies
that
has
the
potential
to
provide
state-of-the-art
sentiment
analysis
abilities
inside
realm
social
media.
Its
software
involves
collection
facts
from
networks,
which
include
Twitter
or
FB,
after
reworking
these
records
into
an
established
format
amenable
NLP
techniques.
The
last
aim
make
automated
predictions
media
posts,
can
be
used
aid
choice-making
methods
customers,
marketers,
researchers,
and
many
others.
As
quantity
data
created
by
users
continues
grow,
so
does
complexity
appropriately
extracting
facts.
allows
for
efficient
automatic
approaches
insights
conversations.
However,
venture
lies
in
finding
extract
sizeable
amount
textual
content
efficaciously.
It
evaluates
discusses
modern
techniques
equipment
apply
analysis.
International Journal of Intelligent Systems,
Journal Year:
2023,
Volume and Issue:
2023, P. 1 - 24
Published: Nov. 13, 2023
Search
engines
are
tools
used
to
find
information
on
the
Internet.
Since
web
has
a
plethora
of
websites,
engine
queries
majority
active
sites
and
builds
database
organized
according
keywords
utilized
in
search.
Because
this,
when
user
types
few
descriptive
words
home
page
search
engine,
function
lists
websites
corresponding
these
keywords.
However,
there
some
problems
with
this
approach.
For
instance,
if
wants
about
word
Jaguar,
most
results
animals
cars.
This
is
polysemic
problem
that
forces
always
provide
popular
but
not
relevant
results.
article
presents
study
using
sentiment
technology
help
news
classification
categorization
improve
accuracy.
We
have
introduced
smart
embedded
into
tackle
issues
record
determine
their
sentimentality.
Therefore,
topic
involves
several
aspects
natural
language
processing
(NLP)
analysis
for
classification.
A
crawler
was
collect
British
Broadcasting
Corporation
(BBC)
across
Internet,
carried
out
preprocessing
text
by
NLP,
applied
methods
polarity
processed
data.
The
sentimentality
represents
negative,
positive,
or
neutral
polarities
assigned
algorithms.
research
BBC
site
different
explore
news.
toolkit
(NLTK)
BM25
indexed
preprocessed
patterns
database.
experimental
depict
proposed
surpassing
normal
an
accuracy
rate
85%.
Moreover,
show
negative
Sentistrength
algorithm.
Furthermore,
Valence
Aware
Dictionary
sEntiment
Reasoner
(VADER)
best-performing
model
obtained
85%
data
collected
function.
Advances in marketing, customer relationship management, and e-services book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 245 - 262
Published: April 19, 2024
Customer
feedback
shapes
businesses
and
improves
customer
experiences
in
the
age
of
advanced
technology
interconnectedness.
This
study
uses
machine
learning
sentiment
analysis
to
gain
insights.
An
efficient
automated
method
analyze
large
volumes
comments,
reviews,
opinions
will
help
make
data-driven
decisions.
The
begins
with
analysis,
learning,
natural
language
processing
theory.
Lexicon-based,
classifier,
deep
methods
are
compared
for
data
handling.
Next,
a
dataset
samples
from
online
sources,
social
media,
review
sites
is
collected.
Preprocessing
handles
noise,
missing
values,
feature
extraction
it
suitable
algorithms.
experimental
phase
several
cutting-edge
models
sentiment.
proposed
work
also
examines
ensemble
transfer
improve
model
performance.
Acta Psychologica,
Journal Year:
2024,
Volume and Issue:
249, P. 104463 - 104463
Published: Aug. 24, 2024
The
study
investigates
the
impact
of
tourist
behavior
change
on
travel
agencies
in
developing
countries,
with
a
focus
strategies
for
enhancing
experience.
research
aims
to
identify
main
factors
influencing
purchasing
and
understand
their
relationship
customer
Data
were
collected
from
368
experienced
tourists
Ho
Chi
Minh
City
Hanoi,
Vietnam,
using
combination
convenience
random
sampling.
Partial
Least
Squares
Structural
Equation
modeling
(PLS-SEM)
is
employed
analyze
model.
findings
confirm
that
product
quality,
price,
brand
image,
marketing
strategy
significantly
influence
behavior.
Importantly,
results
highlight
indirect
effect
these
behavior,
mediated
through
It
suggests
experience
crucial
aspect
decisions.
Based
findings,
industry
managers
agents
countries
should
prioritize
building
strong
personalized
services,
digital
integration,
active
social
media
engagement.
Implementing
dynamic
pricing
targeted
campaigns
address
safety
concerns
local
experiences
are
competitiveness
attracting
travelers
post-crisis.
Future
explore
long-term
effects
agency
performance
adapt
model
specific
regional
contexts.
By
adopting
multifaceted
approaches,
can
enhance
better
navigate
changing
post-crisis
era.
