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Two-wave panel survey dataset on who feels affected by Hurricane Florence
Feeling affected by climate change related natural disasters is an important predictor of engaging in climate change mitigation behavior. We therefore collected data to identify who felt affected by Hurricane Florence, which made landfall in the United States on September 14(th), 2018. In the months...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7548421/ https://www.ncbi.nlm.nih.gov/pubmed/33072829 http://dx.doi.org/10.1016/j.dib.2020.106361 |
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author | Andrews, Talbot M. Smirnov, Oleg |
author_facet | Andrews, Talbot M. Smirnov, Oleg |
author_sort | Andrews, Talbot M. |
collection | PubMed |
description | Feeling affected by climate change related natural disasters is an important predictor of engaging in climate change mitigation behavior. We therefore collected data to identify who felt affected by Hurricane Florence, which made landfall in the United States on September 14(th), 2018. In the months before Hurricane Florence, we collected survey responses from a nationally representative sample of United States citizens. We measured their attitudes towards climate change, emotional predispositions, and demographic information. Then, in the days after the hurricane, we re-contacted respondents to identify whether or not they felt personally affected by Hurricane Florence. These data can be used first to identify variables associated with climate change attitudes, and second to identify the traits that predispose individuals to feel affected by climate change related disasters. |
format | Online Article Text |
id | pubmed-7548421 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-75484212020-10-16 Two-wave panel survey dataset on who feels affected by Hurricane Florence Andrews, Talbot M. Smirnov, Oleg Data Brief Data Article Feeling affected by climate change related natural disasters is an important predictor of engaging in climate change mitigation behavior. We therefore collected data to identify who felt affected by Hurricane Florence, which made landfall in the United States on September 14(th), 2018. In the months before Hurricane Florence, we collected survey responses from a nationally representative sample of United States citizens. We measured their attitudes towards climate change, emotional predispositions, and demographic information. Then, in the days after the hurricane, we re-contacted respondents to identify whether or not they felt personally affected by Hurricane Florence. These data can be used first to identify variables associated with climate change attitudes, and second to identify the traits that predispose individuals to feel affected by climate change related disasters. Elsevier 2020-09-29 /pmc/articles/PMC7548421/ /pubmed/33072829 http://dx.doi.org/10.1016/j.dib.2020.106361 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Andrews, Talbot M. Smirnov, Oleg Two-wave panel survey dataset on who feels affected by Hurricane Florence |
title | Two-wave panel survey dataset on who feels affected by Hurricane Florence |
title_full | Two-wave panel survey dataset on who feels affected by Hurricane Florence |
title_fullStr | Two-wave panel survey dataset on who feels affected by Hurricane Florence |
title_full_unstemmed | Two-wave panel survey dataset on who feels affected by Hurricane Florence |
title_short | Two-wave panel survey dataset on who feels affected by Hurricane Florence |
title_sort | two-wave panel survey dataset on who feels affected by hurricane florence |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7548421/ https://www.ncbi.nlm.nih.gov/pubmed/33072829 http://dx.doi.org/10.1016/j.dib.2020.106361 |
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