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Related Concept Videos

Global Climate Change01:50

Global Climate Change

Throughout its ~4.5 billion year history, the Earth has experienced periods of warming and cooling. However, the current drastic increase in global temperatures is well outside of the Earth’s cyclic norms, and evidence for human-caused global climate change is compelling. Paleoclimatology, the study of ancient climate conditions, provides ample evidence for human-caused global climate change by comparing recent conditions with those in the past.
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Using Generative Art to Convey Past and Future Climate Transitions
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Published on: March 31, 2023

An Image-based Global Climate Sentiment Index.

Xiangyang Zhai1,2, Yunhan Zhang1,2, Shu Zhang1,2,3

  • 1Institutes of Science and Development, Chinese Academy of Sciences, Beijing, China.

Scientific Data
|June 4, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a new Climate Sentiment Index using millions of images, overcoming language barriers to track global public opinion on climate change more accurately.

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Area of Science:

  • Environmental science
  • Climate change research
  • Social science

Background:

  • Climate change impacts necessitate understanding public sentiment for policy and risk management.
  • Existing methods relying on text data face language dependence and cross-country comparability issues.

Purpose of the Study:

  • To develop a globally comparable measure of climate sentiment.
  • To overcome limitations of text-based sentiment analysis by incorporating visual data.
  • To provide a robust tool for monitoring climate attitudes and market expectations.

Main Methods:

  • Collected ~3.19 million climate-related images from 19 countries (2015-2024) via Google Images.
  • Detected positive and negative sentiment within visual data.
  • Constructed a multi-frequency Climate Sentiment Index.

Main Results:

  • Developed a novel Climate Sentiment Index using visual data.
  • Achieved greater accuracy and cross-cultural robustness in sentiment identification.
  • Created a long-horizon, globally comparable dataset.

Conclusions:

  • The visual-data-driven Climate Sentiment Index offers a powerful, language-independent tool.
  • This index enhances understanding of public climate attitudes and market expectations.
  • Applicable across economic, social, and environmental domains for informed decision-making.