Frontiers in Artificial Intelligence,
Journal Year:
2024,
Volume and Issue:
7
Published: Dec. 20, 2024
Social
media
platforms,
including
X,
Facebook,
and
Instagram,
host
millions
of
daily
users,
giving
rise
to
bots
automated
programs
disseminating
misinformation
ideologies
with
tangible
real-world
consequences.
While
bot
detection
in
platform
X
has
been
the
area
many
deep
learning
models
adequate
results,
most
approaches
neglect
graph
structure
social
relationships
often
rely
on
hand-engineered
architectures.
Our
work
introduces
implementation
a
Neural
Architecture
Search
(NAS)
technique,
namely
Deep
Flexible
Graph
(DFG-NAS),
tailored
Relational
Convolutional
Networks
(RGCNs)
task
X.
model
constructs
that
incorporates
both
user
their
metadata.
Then,
DFG-NAS
is
adapted
automatically
search
for
optimal
configuration
Propagation
Transformation
functions
RGCNs.
experiments
are
conducted
TwiBot-20
dataset,
constructing
229,580
nodes
227,979
edges.
We
study
five
architectures
highest
performance
during
achieve
an
accuracy
85.7%,
surpassing
state-of-the-art
models.
approach
not
only
addresses
challenge
but
also
advocates
broader
NAS
neural
network
design
automation.
Cogent Social Sciences,
Journal Year:
2024,
Volume and Issue:
10(1)
Published: Jan. 25, 2024
This
study
explores
the
awareness
of
fake
news
and
trust
dynamics
among
University
students
on
TikTok.
Utilizing
qualitative
research
through
semi-structured
interviews
with
in
Vietnam,
findings
reveal
a
generally
acknowledged
presence
TikTok,
accompanied
by
varying
levels
platform's
content.
Key
factors
influencing
include
content
creator
credibility,
user
engagement,
familiarity
creators.
Beyond
academic
implications,
this
offers
practical
insights
into
digital
literacy,
information
consumption
habits,
susceptibility
to
university
students.
The
advocates
for
heightened
literacy
education,
encouraging
critical
evaluation
online
content,
not
only
benefiting
demographic
but
contributing
broader
public
awareness.
Computers in Human Behavior,
Journal Year:
2023,
Volume and Issue:
150, P. 107992 - 107992
Published: Oct. 17, 2023
This
study
aims
to
investigate
the
association
between
trust
in
institutions
and
reasons
for
sharing
unverified
information
on
social
media.
Specifically,
this
explores
role
of
perceived
self-efficacy
detecting
misinformation
motivation
authenticate
online
contexts.
We
draw
a
sample
2600
respondents,
mainly
Generation
Z
Millennials
(ages
15
30).
The
findings
show
blinding
side
trust,
revealing
positive
media
information.
Trust
is
positively
associated
with
misinformation.
suggest
that
correlation
implies
an
overconfidence
effect
–
i.e.,
individuals
may
overestimate
their
ability
assess
based
belief
source
(institution)
trustworthy.
arguably
represents
tendency
divert
attention
away
from
accuracy
explains
indirect
likelihood
content.
Moreover,
negatively
individuals'
information,
suggesting
rely
utility
rather
than
engage
critical
thinking
verification.
contributes
understanding
spread
by
highlighting
its
It
also
emphasizes
importance
as
mediating
mechanisms.
Journal of the Association for Information Science and Technology,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 13, 2025
Abstract
Fake
news
on
social
media
spreads
faster
and
has
become
a
major
societal
concern,
prompting
numerous
publications
knowledge
sharing
among
researchers.
This
research
aims
to
understand
the
shifting
nature
of
fake
by
investigating
citation
relationships
between
significant
using
key
route
main
path
analysis
(MPA).
The
process
involves
generating
keywords,
collecting
selecting
relevant
data,
conducting
MPA
in
media.
study
analyzes
4.057
from
2010
2023,
identifying
27
influential
works
shaping
diffusion
research.
Findings
reveal
two
phases:
understanding
consumption
patterns
analyzing
its
dissemination
detection
mechanisms.
Through
multiple‐global
MPA,
five
trends
are
identified:
health
misinformation,
fact‐checking,
behavior,
recognition,
physiological
interventions.
shows
continuous
rise
citations,
with
current
focusing
health‐related
misinformation.
offers
insights
into
development
topics
media,
emphasizing
importance
historical
guiding
future
uncovering
trends.
Highlighting
progression
provides
valuable
context,
enabling
more
nuanced
field.
Internet Research,
Journal Year:
2025,
Volume and Issue:
unknown
Published: March 4, 2025
Purpose
Users
contribute
to
online
communities
by
posting
and
responding
discussion
threads.
Nonetheless,
only
a
small
fraction
of
threads
gain
popularity
shape
community
discourse.
Prior
studies
have
identified
several
factors
driving
thread
popularity;
however,
despite
their
prevalence,
the
role
emotional
expressions
within
remains
understudied.
This
study
addresses
this
gap
investigating
impact
starters’
valence
embedded
discrete
emotions
anger,
anxiety
sadness
on
popularity,
drawing
negativity
bias
emotion-as-social-information
theories.
Design/methodology/approach
Using
two
samples
from
Reddit,
employs
negative
binomial
regression
analysis
examine
hypothesized
relationships.
Findings
The
results
demonstrate
that
in
starters
significantly
influences
expression
impacts
variously.
In
some
contexts,
such
as
COVID-19
vaccination
subreddits,
anger
decreases
whereas
sad
enhance
it.
other
professional
discussions
(e.g.
r/Medicine
subreddit),
increase
while
no
significant
influence.
Research
limitations/implications
is
limited
its
focus
specific
contexts.
Future
research
could
broader
range
emotions,
post-content
modalities
cultural
linguistic
differences.
Originality/value
contributes
theory
offering
new
definition
enhancing
our
understanding
discussions.
It
also
provides
practical
implications
for
members
moderators
seeking
promote
posts
help
achieve
goals.
Discourse & Society,
Journal Year:
2024,
Volume and Issue:
35(4), P. 417 - 433
Published: Jan. 28, 2024
In
recent
years,
emotions
have
been
receiving
considerable
attention
in
discourse
analysis,
identified
as
a
defining
feature
of
contemporary
political
discourses.
However,
most
the
previous
studies
field
focused
on
categorization
and
how
these
are
present
texts.
This
approach
fails
if
we
want
to
understand
mechanisms
that
underpin
relevance
discourse,
because
emotion
categories
do
not
tell
us
much
about
why
an
is
constructed
such.
The
purpose
this
article
propose
new
framework
for
more
comprehensive
analysis
drawing
upon
from
sociocognitive
constructivist
perspectives.
Taking
into
account
by
addressee
-and
speaker
or
itself-,
I
methodological
includes
all
elements
play
when
arises.
Example
hate
speech
messages
provided
show
contributions
can
be
made
using
method.
