Journal of Information Science,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 3, 2025
The
Metaverse
represents
a
collaborative
virtual
realm
blending
physical
and
digital
realities,
fostering
limitless
avenues
for
online
interaction,
discovery
innovation.
As
technological
strides
propel
immersive
worlds
to
the
forefront
of
social
media
platforms,
scholarly
interest
in
surges,
prompting
extensive
discourse.
Drawing
from
identity
theory,
this
article
introduces
novel
framework
analysing
polarisation
within
discussions
on
Metaverse,
specifically
X
(Twitter).
Leveraging
multifaceted
approach
that
integrates
clustering,
network
analysis,
text
mining,
our
study
delves
into
both
group
opinion
dynamics
surrounding
Metaverse.
Our
findings
uncover
distinct
community
divisions
structures,
shedding
light
prevalent
themes,
such
as
‘Non-Fungible
Token
(NFTs)’,
‘Virtual
Products
Collections’,
‘Blockchain
Technology’,
‘Gaming’,
‘Financial
Markets’
resonate
public
Nature,
Год журнала:
2024,
Номер
628(8008), С. 582 - 589
Опубликована: Март 20, 2024
Abstract
Growing
concern
surrounds
the
impact
of
social
media
platforms
on
public
discourse
1–4
and
their
influence
dynamics
5–9
,
especially
in
context
toxicity
10–12
.
Here,
to
better
understand
these
phenomena,
we
use
a
comparative
approach
isolate
human
behavioural
patterns
across
multiple
platforms.
In
particular,
analyse
conversations
different
online
communities,
focusing
identifying
consistent
toxic
content.
Drawing
from
an
extensive
dataset
that
spans
eight
over
34
years—from
Usenet
contemporary
media—our
findings
show
conversation
user
behaviour,
irrespective
platform,
topic
or
time.
Notably,
although
long
consistently
exhibit
higher
toxicity,
language
does
not
invariably
discourage
people
participating
conversation,
necessarily
escalate
as
discussions
evolve.
Our
analysis
suggests
debates
contrasting
sentiments
among
users
significantly
contribute
more
intense
hostile
discussions.
Moreover,
persistence
three
decades,
despite
changes
societal
norms,
underscores
pivotal
role
behaviour
shaping
discourse.
Low
uptake
of
the
COVID-19
vaccine
in
US
has
been
widely
attributed
to
social
media
misinformation.
To
evaluate
this
claim,
we
introduce
a
framework
combining
lab
experiments
(total
N
=
18,725),
crowdsourcing,
and
machine
learning
estimate
causal
effect
13,206
vaccine-related
URLs
on
vaccination
intentions
Facebook
users
(
≈
233
million).
We
that
impact
unflagged
content
nonetheless
encouraged
skepticism
was
46-fold
greater
than
misinformation
flagged
by
fact-checkers.
Although
reduced
predicted
significantly
more
when
viewed,
users’
exposure
limited.
In
contrast,
stories
highlighting
rare
deaths
after
were
among
Facebook’s
most-viewed
stories.
Our
work
emphasizes
need
scrutinize
factually
accurate
but
potentially
misleading
addition
outright
falsehoods.
Proceedings of the National Academy of Sciences,
Год журнала:
2024,
Номер
121(21)
Опубликована: Май 13, 2024
We
study
the
effect
of
Facebook
and
Instagram
access
on
political
beliefs,
attitudes,
behavior
by
randomizing
a
subset
19,857
users
15,585
to
deactivate
their
accounts
for
6
wk
before
2020
U.S.
election.
report
four
key
findings.
First,
both
deactivation
reduced
an
index
participation
(driven
mainly
online).
Second,
had
no
significant
knowledge,
but
secondary
analyses
suggest
that
it
knowledge
general
news
while
possibly
also
decreasing
belief
in
misinformation
circulating
online.
Third,
may
have
self-reported
net
votes
Trump,
though
this
does
not
meet
our
preregistered
significance
threshold.
Finally,
effects
affective
issue
polarization,
perceived
legitimacy
election,
candidate
favorability,
voter
turnout
were
all
precisely
estimated
close
zero.
Humanities and Social Sciences Communications,
Год журнала:
2024,
Номер
11(1)
Опубликована: Янв. 13, 2024
Abstract
As
social
media
is
a
key
conduit
for
the
distribution
of
disinformation,
much
literature
on
disinformation
in
elections
has
been
focused
internet
and
global
platforms.
Literature
societal
trust
also
grown
recent
years.
Yet,
not
limited
to
platforms
or
internet,
traditional
outlets
many
European
countries
act
as
vehicles
often
under
direction
government.
Moreover,
connection
between
resilience
less
discussed.
This
article
aimed
at
tackling
question
what
makes
country
vulnerable
resilient
against
online
disinformation.
It
argues
that
society’s
information
can
be
viewed
combination
structural
characteristics,
features
its
knowledge-distribution
institutions
including
system,
activities
capabilities
citizens.
The
this
argument
by
describing
these
dimensions
four
case
countries,
based
comparable
statistics
document
analyses.
results
indicate
European-wide
strategies
do
uniformly
strengthen
national
anti-disinformation
need
anchored
targeted
assessments
state
level
more
effective.
Such
are
central,
particularly
understanding
citizens’
needs
democratic
events
such
elections.
Journal of Economic Literature,
Год журнала:
2024,
Номер
62(4), С. 1422 - 1474
Опубликована: Дек. 1, 2024
We
provide
a
guide
to
the
burgeoning
literature
on
economics
of
social
media.
first
define
media
platforms
and
highlight
their
unique
features.
then
synthesize
main
lessons
from
empirical
organize
them
around
three
stages
life
cycle
content:
(i)
production,
(ii)
distribution,
(iii)
consumption.
Under
we
discuss
how
incentives
affect
content
produced
off
harmful
is
moderated.
network
structure,
algorithms,
targeted
advertisements.
consumption,
affects
individuals
who
consume
its
society
at
large,
explore
consumer
substitution
patterns
across
platforms.
Throughout
guide,
examine
case
studies
deterrence
misinformation,
segregation,
political
advertisements,
effects
outcomes.
conclude
with
brief
discussion
future
(JEL
D12,
D72,
D83,
D91,
I31,
L82,
M37)
Proceedings of the ACM on Human-Computer Interaction,
Год журнала:
2024,
Номер
8(CSCW1), С. 1 - 36
Опубликована: Апрель 17, 2024
Mounting
evidence
indicates
that
the
artificial
intelligence
(AI)
systems
rank
our
social
media
feeds
bear
nontrivial
responsibility
for
amplifying
partisan
animosity:
negative
thoughts,
feelings,
and
behaviors
toward
political
out-groups.
Can
we
design
these
AIs
to
consider
democratic
values
such
as
mitigating
animosity
part
of
their
objective
functions?
We
introduce
a
method
translating
established,
vetted
scientific
constructs
into
AI
functions,
which
term
societal
demonstrate
with
application
science
construct
anti-democratic
attitudes.
Traditionally,
have
lacked
observable
outcomes
use
train
models-however,
sciences
developed
survey
instruments
qualitative
codebooks
constructs,
precision
facilitates
translation
detailed
prompts
large
language
models.
apply
this
create
attitude
model
estimates
extent
post
promotes
attitudes,
test
across
three
studies.
In
Study
1,
first
attitudinal
behavioral
effectiveness
intervention
among
US
partisans
(N=1,380)
by
manually
annotating
(alpha=.895)
posts
scores
testing
several
feed
ranking
conditions
based
on
scores.
Removal
(d=.20)
downranking
(d=.25)
reduced
participants'
without
compromising
experience
engagement.
2,
scale
up
manual
labels
creating
model,
finding
strong
agreement
(rho=.75).
Finally,
in
3,
replicate
1
using
instead
its
impact
(N=558),
again
find
function
(d=.25).
This
presents
novel
strategy
draw
theory
methods
mitigate
harms
AIs.
SSRN Electronic Journal,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
We
review
the
burgeoning
literature
on
economics
of
social
media,
which
has
become
ubiquitous
in
modern
economy
and
fundamentally
changed
how
people
interact.
first
define
media
platforms
isolate
features
that
distinguish
them
from
traditional
other
digital
platforms.
then
synthesize
main
lessons
empirical
organize
around
three
stages
life
cycle
user-generated
content:
(1)
production,
(2)
distribution,
(3)
consumption.
Under
we
discuss
incentives
affect
content
produced
off
harmful
is
moderated.
network
structure,
algorithms,
targeted
advertisements.
consumption,
affects
individuals
who
consume
its
society
at
large,
consumer
substitution
patterns
across
Throughout
review,
delve
into
case
studies
examining
deterrence
misinformation,
segregation,
political
advertisements,
effects
outcomes.
conclude
with
a
brief
discussion
future
media.
Abstract
Social
media
ranking
algorithms
typically
optimize
for
users’
revealed
preferences,
i.e.
user
engagement
such
as
clicks,
shares,
and
likes.
Many
have
hypothesized
that
by
focusing
on
these
may
exacerbate
human
behavioral
biases.
In
a
preregistered
algorithmic
audit,
we
found
that,
relative
to
reverse-chronological
baseline,
Twitter’s
engagement-based
algorithm
amplifies
emotionally
charged,
out-group
hostile
content
users
say
makes
them
feel
worse
about
their
political
out-group.
Furthermore,
find
do
not
prefer
the
tweets
selected
algorithm,
suggesting
underperforms
in
satisfying
stated
preferences.
Finally,
explore
implications
of
an
alternative
approach
ranks
based
preferences
reduction
angry,
partisan,
content,
but
also
potential
reinforcement
proattitudinal
content.
Overall,
our
findings
suggest
greater
integration
into
social
could
promote
better
online
discourse,
though
trade-offs
warrant
further
investigation.
Scientific Reports,
Год журнала:
2024,
Номер
14(1)
Опубликована: Янв. 11, 2024
Abstract
As
scientists,
we
are
proud
of
our
role
in
developing
the
current
digital
age
that
enables
billions
people
to
communicate
rapidly
with
others
via
social
media.
However,
when
things
go
wrong,
also
responsible
for
taking
an
ethical
stand
and
trying
solve
problems,
this
work
aims
take
a
step
direction.
Our
goal
is
set
foundation
mathematically
formal
study
how
might
regulate
media
and,
particular,
address
problem
echo
chamber
effect.
An
closed
system
where
other
voices
excluded
by
omission,
causing
your
beliefs
become
amplified
or
reinforced.
In
turn,
these
bubbles
can
boost
polarization
extreme
political
views,
unfortunately,
there
strong
evidence
chambers
exist
The
fundamental
question
try
answer
is:
regulation
“break”
reduce
effect
media?
Sadly,
paper’s
main
result
impossibility
result:
general
function
achieves
(on
model)
while
obeying
core
values
democratic
societies
(freedom
expression
user
privacy)
does
not
exist.
This
leaves
us
hard
future
choices
make.