{"title":"Feeling the heat? Analyzing climate change sentiment in Spain using Twitter data","authors":"Maria L. Loureiro , Maria Alló","doi":"10.1016/j.reseneeco.2024.101437","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":47952,"journal":{"name":"Resource and Energy Economics","volume":"77 ","pages":"Article 101437"},"PeriodicalIF":2.6000,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Resource and Energy Economics","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0928765524000137","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍：
Resource and Energy Economics provides a forum for high level economic analysis of utilization and development of the earth natural resources. The subject matter encompasses questions of optimal production and consumption affecting energy, minerals, land, air and water, and includes analysis of firm and industry behavior, environmental issues and public policies. Implications for both developed and developing countries are of concern. The journal publishes high quality papers for an international audience. Innovative energy, resource and environmental analyses, including theoretical models and empirical studies are appropriate for publication in Resource and Energy Economics.
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