Impact of temperature on expressed sentiments in social media: evidence from a Latin American country
Environment and Development Economics,
Год журнала:
2025,
Номер
unknown, С. 1 - 25
Опубликована: Апрель 7, 2025
Abstract
This
study
examines
the
impact
of
temperature
on
human
well-being
using
approximately
80
million
geo-tagged
tweets
from
Argentina
spanning
2017–2022.
Employing
text
mining
techniques,
we
derive
two
quantitative
estimators:
sentiments
and
a
social
media
aggression
index.
The
Hedonometer
Index
measures
overall
sentiment,
distinguishing
positive
negative
ones,
while
aggressive
behavior
is
assessed
through
profanity
frequency.
Non-linear
fixed
effects
panel
regressions
reveal
notable
causal
association
between
extreme
heat
sentiment
index,
with
weaker
relationship
found
for
cold.
Our
results
highlight
that,
strongly
influences
sentiments,
it
has
no
significant
effect
ones.
Consequently,
extremely
high
temperatures
predominantly
driven
by
heightened
feelings
in
hot
conditions.
Moreover,
our
index
exhibits
similar
pattern
to
that
observed
sentiments.
Язык: Английский
The impact of climatic factors on negative sentiments: An analysis of human expressions from X platform in Germany
iScience,
Год журнала:
2025,
Номер
28(3), С. 111966 - 111966
Опубликована: Фев. 8, 2025
Expressions
in
social
media
can
provide
a
rapid
insight
into
people's
reactions
to
events,
such
as
periods
of
climatic
stress.
This
study
explored
the
link
between
stressors
and
negative
sentiment
on
X
platform
Germany
inform
climate-related
health
policies
interventions.
Natural
language
processing
was
used
standardize
text,
comprehensive
approach
for
analysis
utilized.
We
then
conducted
spatiotemporal
modeling
fitted
using
integrated
nested
laplace
approximation
(INLA).
Our
findings
indicate
that
higher
lower
level
temperature
precipitation
is
correlated
with
an
increase
decrease
relative
risk
sentiments,
respectively.
The
this
illustrate
human
distress
varies
space
time
about
exposure
climate
stressors.
emotional
indicator
responses
stress
indicates
potential
physical
mental
impacts
among
affected
populations.
Язык: Английский
Spatial heterogeneities of residents' sentiments and their associations with urban functional areas during heat waves– a case study in Beijing
Computational Urban Science,
Год журнала:
2024,
Номер
4(1)
Опубликована: Март 11, 2024
Abstract
The
intensification
of
global
heat
wave
events
is
seriously
affecting
residents'
emotional
health.
Based
on
social
media
big
data,
our
research
explored
the
spatial
pattern
sentiments
during
waves
(SDHW).
Besides,
their
association
with
urban
functional
areas
(UFAs)
was
analyzed
using
Apriori
algorithm
rule
mining.
It
found
that
SDHW
in
Beijing
were
characterized
by
obvious
clustering,
hot
spots
predominately
dispersed
and
far
suburbs,
cold
mainly
clustered
near
suburbs.
As
for
associations
function
areas,
green
space
park
had
significant
effects
positive
sentiment
study
area,
while
a
higher
percentage
industrial
greater
impact
negative
SDHW.
When
it
comes
to
combined
UFAs,
results
revealed
area
other
more
closely
related
SDHW,
indicating
significance
promoting
sentiment.
Subdistricts
lower
residential
traffic
may
have
There
two
main
UFAs
impacts
SDHW:
combination
public
areas.
This
contributes
understanding
improving
community
planning
governance
when
increase,
building
healthy
cities,
enhancing
emergency
management.
Язык: Английский
The Impact of Climate on Negative Sentiments: An Analysis of Human Expressions on the X Platform in Germany
Опубликована: Янв. 1, 2024
Expressions
in
social
media
can
provide
a
rapid
insight
into
people's
reaction
to
events,
such
as
periods
of
climatic
stress.
We
investigated
the
relationship
between
stressors,
and
negative
sentiment
expressions
on
X
platform
from
Germany.
Natural
language
processing
was
conducted
facilitate
cleaning
standardizing
text
or
tweets,
comprehensive
approach
for
analysis
utilized.
then
spatiotemporal
modelling
fitted
using
Integrated
Nested
Laplace
Approximation
(INLA).
Our
findings
indicate
that
higher
lower
level
temperature
precipitation
is
correlated
with
an
increase
decrease
relative
risk
sentiments
respectively.
The
this
study
illustrate
human
distress
varies
space
time
relation
exposure
climate
stressors.
This
emotional
indicator
responses
stress
indicates
potential
physical
mental
health
impacts
among
affected
populations.
Язык: Английский