Feeling the heat? Analyzing climate change sentiment in Spain using Twitter data

Maria Loureiro and Maria Alló

Resource and Energy Economics, 2024, vol. 77, issue C

Abstract: To shed light on the recent debate about climate change in this post-pandemic scenario, we take advantage of a unique dataset that combines geo-tagged social media data from Twitter in Spain from 2017 to 2022. Twitter conversations have been analyzed with natural language processing techniques to obtain sentiment scores related to climate change. These were merged with additional relevant control variables, aiming to understand the role of the contributing factors on the evolution of the hedonic scores, including external temperatures, the occurrence of heat waves, and deaths related to climate. We find a strong negative effect of external temperatures on sentiment, aggravated by recent increases in the frequency of heat waves and deaths related to climate. Further, this negative sentiment is accentuated after experiencing the recent COVID-19.

Keywords: Climate change; LabMT; Natural language processing; Sentiment analysis; Social media; VADER (search for similar items in EconPapers)
JEL-codes: Q50 Q51 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:resene:v:77:y:2024:i:c:s0928765524000137

DOI: 10.1016/j.reseneeco.2024.101437

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