Applied Sciences,
Journal Year:
2025,
Volume and Issue:
15(6), P. 3184 - 3184
Published: March 14, 2025
With
the
rapid
integration
of
artificial
intelligence
(AI)
technologies
in
field
education,
public
sentiment
towards
this
development
has
gradually
emerged
as
an
important
area
research.
This
study
focuses
on
analysis
online
opinions
regarding
application
AI
education.
Python
was
used
to
scrape
relevant
comments
from
various
provinces
China.
Using
SnowNLP
algorithm,
sentiments
were
classified
into
three
categories:
positive,
neutral,
and
negative.
The
primarily
analyzes
spatial
distribution
characteristics
positive
negative
sentiments,
with
a
visualization
results
through
Geographic
Information
Systems
(GIS).
Additionally,
Moran’s
I
Getis-Ord
Gi*
are
introduced
detect
autocorrelation
attitudes.
Furthermore,
by
constructing
multivariable
geographical
detector
model
MGWR,
explores
impact
factors
such
digital
economy,
construction
smart
cities,
local
government
policy
attention,
literacy
residents,
level
education
infrastructure
research
will
reveal
regional
disparities
education-related
its
driving
mechanisms,
providing
data
support
empirical
references
for
optimizing
Frontiers in Sports and Active Living,
Journal Year:
2025,
Volume and Issue:
7
Published: Feb. 10, 2025
Introduction
Sports
fans'
curiosity
and
impulsive
buying
tendencies
are
important
topics
in
sports
marketing,
yet
the
mediating
role
of
social
media
use
intensity
linking
these
variables
remains
underexplored.
Grounded
Stimulus-Organism-Response
(S-O-R)
theory,
this
study
examines
how
mediates
relationship
between
behavior.
Methods
The
sampled
623
Taiwanese
fans,
including
baseball
basketball
enthusiasts,
to
investigate
relationships.
Structural
Equation
Modeling
(SEM)
was
employed
test
proposed
hypotheses,
focusing
on
effect
intensity.
Results
results
indicate
that
fully
tendencies.
This
highlights
significant
digital
engagement
shaping
consumer
behavior
among
fans.
Discussion
These
findings
emphasize
importance
fostering
as
a
strategic
tool
marketing.
By
transforming
into
tangible
purchasing
behavior,
provides
valuable
theoretical
practical
contributions
understanding
fan
offers
actionable
recommendations
for
marketers
seeking
enhance
their
marketing
strategies
era.
Journal of Consumer Marketing,
Journal Year:
2025,
Volume and Issue:
unknown
Published: March 3, 2025
Purpose
Homophily,
a
prominent
phenomenon
in
social
networking,
profoundly
shapes
user
behaviors
on
media
but
has
not
been
well
studied
the
livestream
commerce
context.
This
study
aims
to
investigate
its
moderation
role
leveraging
effects
of
key
factors
–
perceived
expertise
live
streamers
and
interaction
during
streaming
audience
trust,
critical
determinant
purchase
intentions.
Design/methodology/approach
A
survey
was
conducted
among
shoppers
Taobao.
sample
313
responses
analyzed.
SPSS
(version
29)
used
for
general
statistical
analysis.
The
partial
least
squares
structural
equation
modeling
approach
with
SmartPLS
4.1
software
assess
research
model
hypotheses.
Findings
results
reveal
noteworthy
differential
homophily:
it
negatively
moderates
expertise–trust
association
positively
interaction–trust
relationship.
When
perceives
strong
homophily
streamers,
their
trust
these
becomes
increasingly
contingent
level
interaction,
whereas
effect
diminishes.
Originality/value
insights
are
novel
literature.
These
findings
extend
theoretical
understanding
provide
valuable
guidance
marketers
platforms
seeking
reinforce
drive
intentions
commerce.
Applied Sciences,
Journal Year:
2025,
Volume and Issue:
15(6), P. 3184 - 3184
Published: March 14, 2025
With
the
rapid
integration
of
artificial
intelligence
(AI)
technologies
in
field
education,
public
sentiment
towards
this
development
has
gradually
emerged
as
an
important
area
research.
This
study
focuses
on
analysis
online
opinions
regarding
application
AI
education.
Python
was
used
to
scrape
relevant
comments
from
various
provinces
China.
Using
SnowNLP
algorithm,
sentiments
were
classified
into
three
categories:
positive,
neutral,
and
negative.
The
primarily
analyzes
spatial
distribution
characteristics
positive
negative
sentiments,
with
a
visualization
results
through
Geographic
Information
Systems
(GIS).
Additionally,
Moran’s
I
Getis-Ord
Gi*
are
introduced
detect
autocorrelation
attitudes.
Furthermore,
by
constructing
multivariable
geographical
detector
model
MGWR,
explores
impact
factors
such
digital
economy,
construction
smart
cities,
local
government
policy
attention,
literacy
residents,
level
education
infrastructure
research
will
reveal
regional
disparities
education-related
its
driving
mechanisms,
providing
data
support
empirical
references
for
optimizing
