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.

Biology Centre of the Czech Academy of Sciences Institute of Hydrobiology Ceske Budejovice Czech Republic

BIOPOLIS Program in Genomics Biodiversity and Land Planning CIBIO Campus de Vairão Vairão 4485 661 Portugal

Centre for the Research and Technology of Agroenvironmental and Biological Sciences CITAB Institute for Innovation Capacity Building and Sustainability of Agri food Production Inov4Agro Universidade de Trás os_montes e Alto Douro UTAD Vila Real 500 801 Portugal

CIBIO Centro de Investigação em Biodiversidade e Recursos Genéticos InBIO Laboratório Associado Campus de Vairão Universidade do Porto Vairão 4485 661 Portugal

Departamento de Anatomía Biología Celular y Zoología Facultad de Ciencias Universidad de Extremadura Badajoz Spain

Departamento de Biologia Faculdade de Ciências Universidade do Porto Porto 4099 002 Portugal

Ecología en el Antropoceno Facultad de Ciencias Unidad Asociada CSIC UEX Universidad de Extremadura Badajoz Spain

Faculty of Sciences University of Porto Rua do Campo Alegre Porto Porto 4169 007 Portugal

Instituto Universitário de Lisboa CIS IUL Lisbon Portugal

LIAAD INESC TEC Rua Dr Roberto Frias Porto Porto 4200 465 Portugal

NBI Natural Business Intelligence Régia Douro Park Andrães Vila Real 5000 033 Portugal

Université Paris Saclay CNRS AgroParisTech Ecologie Systématique Evolution Gif sur Yvette France

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