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Mapping climate discourse to climate opinion: An approach for augmenting surveys with social media to enhance understandings of climate opinion in the United States
- Source :
- PLoS ONE, PLoS ONE, Vol 16, Iss 1, p e0245319 (2021), PLOS ONE
- Publication Year :
- 2020
-
Abstract
- Surveys are commonly used to quantify public opinions of climate change and to inform sustainability policies. However, conducting large-scale population-based surveys is often a difficult task due to time and resource constraints. This paper outlines a machine learning framework—grounded in statistical learning theory and natural language processing—to augment climate change opinion surveys with social media data. The proposed framework maps social media discourse to climate opinion surveys, allowing for discerning the regionally distinct topics and themes that contribute to climate opinions. The analysis reveals significant regional variation in the emergent social media topics associated with climate opinions. Furthermore, significant correlation is identified between social media discourse and climate attitude. However, the dependencies between topic discussion and climate opinion are not always intuitive and often require augmenting the analysis with a topic’s most frequent n-grams and most representative tweets to effectively interpret the relationship. Finally, the paper concludes with a discussion of how these results can be used in the policy framing process to quickly and effectively understand constituents’ opinions on critical issues.
- Subjects :
- Atmospheric Science
010504 meteorology & atmospheric sciences
Climate
Social Sciences
010501 environmental sciences
Surveys
01 natural sciences
Global Warming
Machine Learning
Mathematical and Statistical Techniques
Sociology
Surveys and Questionnaires
Climatology
education.field_of_study
Multidisciplinary
Geography
Statistics
Social Communication
Public relations
Social Networks
Research Design
Physical Sciences
Medicine
Natural language
Algorithms
Network Analysis
Research Article
Computer and Information Sciences
Process (engineering)
Science
Climate Change
Population
Twitter
Climate change
Research and Analysis Methods
Artificial Intelligence
Social media
Statistical Methods
education
0105 earth and related environmental sciences
Motivation
Survey Research
business.industry
Samfunnsvitenskap: 200 [VDP]
Global warming
Models, Theoretical
United States
Communications
Framing (social sciences)
Attitude
13. Climate action
Sustainability
Earth Sciences
Anthropogenic Climate Change
business
Social Media
Mathematics
Forecasting
Subjects
Details
- ISSN :
- 19326203
- Volume :
- 16
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- PloS one
- Accession number :
- edsair.doi.dedup.....7566647dc14c6d3345e91c70082fa352