Journal of Information Science,
Год журнала:
2022,
Номер
50(5), С. 1085 - 1097
Опубликована: Авг. 29, 2022
This
article
studies
how
sentiment
strength
and
cognitive
language
may
influence
the
levels
of
tweet
virality.
A
total
11,381
tweets
about
a
horror
movie
(‘Mother!’)
were
collected.
Based
on
definitions
two
independent
variables:
use,
dependent
variable:
virality,
data
descriptive
statistics
analysis
variance
(ANOVA)
applied
to
reveal
relationships
between
virality
factors.
The
results
indicate
that
high
is
associated
with
either
lower
level
or/and
higher
use
by
statistically
significant
margin.
finding
more
evident
for
negative
tweets.
study
findings
help
improve
understanding
sentimental
factors
impacting
guide
industry
marketing
content
achieve
social
media.
conclusions
can
also
be
other
industries,
government
agencies,
organisations
individuals
who
intend
quickly
disseminate
specific
information
media
platforms.
Applied Sciences,
Год журнала:
2022,
Номер
12(22), С. 11775 - 11775
Опубликована: Ноя. 19, 2022
Twitter
has
become
a
major
social
media
platform
and
attracted
considerable
interest
among
researchers
in
sentiment
analysis.
Research
into
Sentiment
Analysis
(TSA)
is
an
active
subfield
of
text
mining.
TSA
refers
to
the
use
computers
process
subjective
nature
data,
including
its
opinions
sentiments.
In
this
research,
thorough
review
most
recent
developments
area,
wide
range
newly
proposed
algorithms
applications
are
explored.
Each
publication
arranged
category
based
on
significance
particular
type
method.
The
purpose
survey
provide
concise,
nearly
comprehensive
overview
techniques
related
fields.
primary
contributions
detailed
classifications
numerous
articles
depiction
current
direction
research
field
TSA.
Frontiers in Public Health,
Год журнала:
2023,
Номер
11
Опубликована: Авг. 17, 2023
Vaccination
is
widely
regarded
as
the
paramount
approach
for
safeguarding
individuals
against
repercussions
of
COVID-19.
Nonetheless,
concerns
surrounding
efficacy
and
potential
adverse
effects
these
vaccines
have
become
prevalent
among
public.
To
date,
there
has
been
a
paucity
research
investigating
public
perceptions
adoption
COVID-19
vaccines.
Therefore,
present
study
endeavours
to
address
this
lacuna
by
undertaking
spatiotemporal
analysis
sentiments
towards
vaccination
its
uptake
in
England
at
local
authority
level,
while
concurrently
examining
sociodemographic
attributes
national
level.A
sentiment
Twitter
data
was
undertaken
delineate
distribution
positive
their
demographic
correlates.
Positive
were
categorized
into
clusters
streamline
comparison
across
different
age
gender
demographics.
The
relationship
between
evaluated
using
Spearman's
correlation
coefficient.
Additionally,
bivariate
carried
out
further
probe
rates.The
results
indicated
that
majority
tweets
posted
males,
although
females
expressed
higher
levels
sentiment.
group
over
40
dominated
exhibited
highest
polarity.
positively
correlated
with
number
level.Overall,
opinions
on
are
predominantly
positive.
receiving
vaccinations
level
prevalence
attitudes
vaccines,
particularly
population
aged
40.
These
findings
suggest
targeted
efforts
increase
younger
populations,
necessary
achieve
widespread
coverage.
IEEE Transactions on Computational Social Systems,
Год журнала:
2023,
Номер
11(3), С. 3550 - 3579
Опубликована: Окт. 27, 2023
Microblogging
site
Twitter
(re-branded
to
X
since
July
2023)
is
one
of
the
most
influential
online
social
media
websites,
which
offers
a
platform
for
masses
communicate,
expresses
their
opinions,
and
shares
information
on
wide
range
subjects
products,
resulting
in
creation
large
amount
unstructured
data.
This
has
attracted
significant
attention
from
researchers
who
seek
understand
analyze
sentiments
contained
within
this
massive
user-generated
text.
The
task
sentiment
analysis
(SA)
entails
extracting
identifying
user
opinions
text,
various
lexicon-and
machine
learning-based
methods
have
been
developed
over
years
accomplish
this.
However,
deep
learning
(DL)-based
approaches
recently
become
dominant
due
superior
performance.
study
briefs
standard
preprocessing
techniques
word
embeddings
data
preparation.
It
then
delves
into
taxonomy
provide
comprehensive
summary
DL-based
approaches.
In
addition,
work
compiles
popular
benchmark
datasets
highlights
evaluation
metrics
employed
performance
measures
resources
available
public
domain
aid
SA
tasks.
Furthermore,
survey
discusses
domain-specific
practical
applications
Finally,
concludes
with
research
challenges
outlines
future
outlooks
further
investigation.
Discover Psychology,
Год журнала:
2024,
Номер
4(1)
Опубликована: Ноя. 18, 2024
Despite
the
formal
declaration
of
end
global
health
emergency
related
to
COVID-19,
disease
continues
pose
significant
challenges
worldwide.
This
study
addresses
gap
in
existing
literature
regarding
impact
COVID-19
anxiety
on
university
students
during
peak
pandemic.
Specifically,
it
examined
how
influenced
meaning
life,
life
orientation,
and
academic
motivation;
variables
that
are
known
predictors
student
success
their
overall
well-being.
Conducted
as
a
non-experimental
quantitative
cross-sectional
study,
data
were
collected
from
557
participants
selected
through
purposive
sampling.
The
research
used
Coronavirus
Pandemic
Anxiety
Scale,
Academic
Motivation
Revised
Life
Orientation
Test,
Meaning
Questionnaire
gather
relevant
data.
Findings
reveal
has
negative
influence
motivation,
presence
meaning,
orientation.
results
also
indicate
positive
relationship
between
search
for
life.
These
findings
not
only
enhance
understanding
pandemic's
adverse
impacts
but
provide
basis
future
interventions
strategies
by
educational
stakeholders
policymakers
aimed
at
mitigating
these
effects.
