The association of climate-induced stressors on risk of negative sentiment: An analysis from 462 million geotagged tweets in Europe

This study examines how climate-induced health risks influence negative sentiments on European social tweets from 2015 to 2022. Analyzing over 400 million tweets using NLP tools (NLTK, LIWC22) and spatial-temporal aggregation at the NUTS2 weekly level, we applied a Poisson generalized additive model (GAM) with integrated nested Laplace approximation (INLA) and fused lasso regularization to capture sentiment fluctuations. Results show negative sentiments rise by up to 0.36% when maximum temperatures exceed 26.9°C and by 0.49% during severe droughts (SPI < -3.72). Elevated alder pollen counts (>135 grains/m<sup>3</sup>) also increase risk of negative sentiment by 0.21%, while temperatures below 2.9°C reduce it by 0.63%. No significant association was found with heat-related mortality or West Nile virus incidence. These findings suggest specific climate-related health factors-high temperatures, droughts, and pollen-trigger negative social media reactions, whereas others, such as mortality and infectious outbreaks, appear unnoticed in public sentiment.

Authors

Institutions

Publication Details

Journal
iScience
Published
2025-11-05
DOI
https://doi.org/10.1016/j.isci.2025.113933
Primary Topic
Climate Change Communication and Perception
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The association of climate-induced stressors on risk of negative sentiment: An analysis from 462 million geotagged tweets in Europe

Till Bärnighausen, Joan Ballester, Stella Dafka, Marina Romanello et al.
iScience
Climate Change Communication and Perception
article

The association of climate-induced stressors on risk of negative sentiment: An analysis from 462 million geotagged tweets in Europe

Till Bärnighausen, Joan Ballester, Stella Dafka, Marina Romanello, Elisa Gallo, Mikhail A. Sofiev, Barrak Alahmad, Tareq Mohammed Ali AL-Ahdal, Michael Gertz, Joacim Rocklöv, Sandra Barman
article en

Abstract

This study examines how climate-induced health risks influence negative sentiments on European social tweets from 2015 to 2022. Analyzing over 400 million tweets using NLP tools (NLTK, LIWC22) and spatial-temporal aggregation at the NUTS2 weekly level, we applied a Poisson generalized additive model (GAM) with integrated nested Laplace approximation (INLA) and fused lasso regularization to capture sentiment fluctuations. Results show negative sentiments rise by up to 0.36% when maximum temperatures exceed 26.9°C and by 0.49% during severe droughts (SPI < -3.72). Elevated alder pollen counts (>135 grains/m<sup>3</sup>) also increase risk of negative sentiment by 0.21%, while temperatures below 2.9°C reduce it by 0.63%. No significant association was found with heat-related mortality or West Nile virus incidence. These findings suggest specific climate-related health factors-high temperatures, droughts, and pollen-trigger negative social media reactions, whereas others, such as mortality and infectious outbreaks, appear unnoticed in public sentiment.

iScienceVol. 28(12)
Finnish Meteorological Institute (FI), Harvard University (US), Heidelberg University (DE), RISE Research Institutes of Sweden (SE), University Hospital Heidelberg (DE), Barcelona Institute for Global Health (ES), University College London (GB), Heidelberg University (US), Umeå University (SE)
Openalex Percentile: Top 58%
Climate Change Communication and Perception
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.