Effective text classification using BERT, MTM LSTM, and DT
Data & Knowledge Engineering,
Год журнала:
2024,
Номер
151, С. 102306 - 102306
Опубликована: Апрель 21, 2024
Язык: Английский
Evolving techniques in sentiment analysis: a comprehensive review
PeerJ Computer Science,
Год журнала:
2025,
Номер
11, С. e2592 - e2592
Опубликована: Янв. 28, 2025
With
the
rapid
expansion
of
social
media
and
e-commerce
platforms,
an
unprecedented
volume
user-generated
content
has
emerged,
offering
organizations,
governments,
researchers
invaluable
insights
into
public
sentiment.
Yet,
vast
unstructured
nature
this
data
challenges
traditional
analysis
methods.
Sentiment
analysis,
a
specialized
field
within
natural
language
processing,
evolved
to
meet
these
by
automating
detection
categorization
opinions
emotions
in
text.
This
review
comprehensively
examines
evolving
techniques
sentiment
detailing
foundational
processes
such
as
gathering
feature
extraction.
It
explores
spectrum
methodologies,
from
classical
word
embedding
machine
learning
algorithms
recent
contextual
advanced
transformer
models
like
Generative
Pre-trained
Transformer
(GPT),
Bidirectional
Encoder
Representations
Transformers
(BERT),
T5.
critical
comparison
methods,
article
highlights
their
appropriate
uses
limitations.
Additionally,
provides
thorough
overview
current
trends,
future
directions,
exploration
unresolved
challenges.
By
synthesizing
developments,
equips
with
solid
foundation
for
assessing
state
guiding
advancements
dynamic
field.
Язык: Английский
A joint-training topic model for social media texts
Humanities and Social Sciences Communications,
Год журнала:
2025,
Номер
12(1)
Опубликована: Март 1, 2025
Язык: Английский
Sentiment Analysis in Employee Experience Using Natural Language Processing and Machine Learning
Advances in human resources management and organizational development book series,
Год журнала:
2025,
Номер
unknown, С. 309 - 346
Опубликована: Янв. 24, 2025
This
chapter
focuses
on
the
use
of
sentiment
analysis
in
handling
employee
experience.
When
organisations
start
thinking
about
experience
their
employees
as
a
factor
that
influences
performance
and
turnover,
provides
quantitative
way
measuring
emotions,
satisfaction
engagement
employees.
attentions
several
NLP
techniques
can
be
employed
feedback
which
include
tokenization,
stop-word
removal
vectorization.
It
also
looks
at
how
other
machine
learning
models
such
Naive
Bayes,
Support
Vector
Machines,
Long
Short-Term
Memory
used
to
categorize
emotions
positive,
negative,
or
neutral.
In
addition,
problem
language,
culture,
data
bias
is
described,
ways
solve
them
are
described.
The
future
potential
real-time
emotion
along
with
organizational
KPIs
for
improving
management
employees'
depicted.
Язык: Английский
Harnessing Linguistic Analysis for ADHD Diagnosis Support: A Stylometric Approach to Self-Defining Memories
Опубликована: Апрель 24, 2024
This
study
explores
the
potential
of
stylometric
analysis
in
identifying
Self-Defining
Memories
(SDMs)
authored
by
individuals
with
Attention-Deficit/Hyperactivity
Disorder
(ADHD)
versus
a
control
group.
A
sample
198
SDMs
were
written
66
adolescents
and
then
analysed
using
Support
Vector
Classifiers
(SVC).
The
included
variety
linguistic
features
such
as
character
3-grams,
function
words,
sentence
length,
or
lexical
richness
among
others.
It
also
metadata
about
participants
(gender,
age)
their
(self-reported
sentiment
after
recalling
memories).
results
reveal
promising
ability
to
accurately
classify
SDMs,
perfect
prediction
(F1=1.0)
contextually
simpler
setup
text-by-text
prediction,
satisfactory
levels
precision
(F1
=
0.77)
when
predicting
individual
individual.
Such
highlight
significant
role
that
characteristics
play
reflecting
distinctive
cognitive
patterns
associated
ADHD.
While
not
substitute
for
professional
diagnosis,
textual
offers
supportive
avenue
early
detection
deeper
understanding
Язык: Английский
Quantum theory-inspired inter-sentence semantic interaction model for textual adversarial defense
Complex & Intelligent Systems,
Год журнала:
2024,
Номер
11(1)
Опубликована: Дек. 30, 2024
Abstract
Deep
neural
networks
have
a
recognized
susceptibility
to
diverse
forms
of
adversarial
attacks
in
the
field
natural
language
processing
and
such
security
issue
poses
substantial
risks
erodes
trust
artificial
intelligence
applications
among
people
who
use
them.
Meanwhile,
quantum
theory-inspired
models
that
represent
word
composition
as
mixture
words
modeled
non-linear
semantic
interaction.
However,
modeling
without
considering
interaction
between
sentences
current
literature
does
not
exploit
potential
probabilistic
description
for
improving
robustness
settings.
In
present
study,
novel
inter-sentence
model
is
proposed
enhancing
via
fusing
contextual
semantics.
More
specifically,
it
analyzed
why
humans
are
able
understand
textual
examples,
crucial
point
observed
adept
at
associating
information
from
context
comprehend
paragraph.
Guided
by
this
insight,
input
text
segmented
into
subsentences,
with
simulating
comprehension
representing
each
subsentence
particle
within
system,
utilizing
density
matrix
interactions.
A
loss
function
integrating
cross-entropy
orthogonality
losses
employed
encourage
measurement
states.
Comprehensive
experiments
conducted
validate
efficacy
methodology,
results
underscore
its
superiority
over
baseline
even
commercial
based
on
large
terms
accuracy
across
attack
scenarios,
showing
approach
under
attacks.
Язык: Английский
Arduino-Based Alcohol Detection Device: Enhancing Safety in Vehicle Operation through Sensor Technology
Asian Journal of Applied Science and Technology,
Год журнала:
2024,
Номер
08(01), С. 133 - 150
Опубликована: Янв. 1, 2024
In
this
context,
an
Arduino-based
alcohol
detector
is
example
of
a
device
that
has
the
potential
to
detect
presence
in
surrounding
environment.
It
possible
use
tool
check
results
individuals
who
have
drank
while
operating
motor
vehicle.
A
MQ-3
sensor
utilized
by
order
ascertain
whether
or
not
readily
available.
The
component
constitutes
heats
layer
conducting
material
simultaneously
measuring
resistance
substrate.
There
change
whenever
it
subjected
scents
vapors
alcohol.
Signals
both
digital
and
analogue
types
can
be
obtained
from
sensor.
distinction
made
between
two
very
plain
way.
are
only
conceivable
states
output
take
communicating
with
microcontroller.
These
high
low,
which
means
they
represent
values
1
0,
respectively.
An
analog
signal,
on
other
hand,
received
microcontroller,
provides
indication
amount
present
environment
utilizing
wide
range
values,
ranging
0
1023.
LED,
sensor,
Arduino
Uno
components
required
construct
device.
confined
areas
for
showing
straightforward
applications
small
scale,
performs
admirably.
process
installing
gadget
vehicles
yet
another
approach
may
used
lessen
number
accidents
caused
drunk
driving.
addition
being
user-friendly
easy
repair,
level
sensitivity
Язык: Английский