Harnessing deep learning to monitor people's perceptions towards climate change on social media

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60077344%3A_____%2F25%3A00646899" target="_blank" >RIV/60077344:_____/25:00646899 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1038/s41598-025-97441-1" target="_blank" >https://doi.org/10.1038/s41598-025-97441-1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41598-025-97441-1" target="_blank" >10.1038/s41598-025-97441-1</a>

Result language

angličtina

Original language name

Harnessing deep learning to monitor people's perceptions towards climate change on social media

Original language description

Social media has become a popular stage for people's views over climate change. Monitoring how climate change is perceived on social media is relevant for informed decision-making. This work advances the way social media users' perceptions and reactions towards climate change can be understood over time, by implementing a scalable methodological framework grounded on natural language processing. The framework was tested in over 1771 thousand X/Twitter posts of Spanish, Portuguese, and English discourses from Southwestern Europe. The employed models were successful (i.e., > 84% success rate) in detecting relevant climate change posts. The methodology detected specific climate phenomena in users' discourse, coinciding with the occurrence of major climatic events in the test area (e.g., wildfires, storms). The classification of sentiments, emotions, and irony was also efficient, with evaluation metrics ranging from 71 to 92%. Most users' reactions were neutral (> 35%) or negative (> 39%), mostly associated to sentiments of anger and sadness over climate impacts. Almost a quarter of posts showed ironic content, reflecting the common use of irony in social media communication. Our exploratory study holds potential to support climate decisions based on deep learning tools from monitoring people's perceptions towards climate issues in the online space.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

50802 - Media and socio-cultural communication

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Scientific Reports

ISSN

2045-2322

e-ISSN

2045-2322

Volume of the periodical

15

Issue of the periodical within the volume

1

Country of publishing house

GB - UNITED KINGDOM

Number of pages

13

Pages from-to

14924

UT code for WoS article

001478481100019

EID of the result in the Scopus database

2-s2.0-105003819873