Internet image search outputs propagate climate change sentiment and impact policy support

Michael Berkebile-Weinberg (), Runji Gao, Rachel Tang and Madalina Vlasceanu ()
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Michael Berkebile-Weinberg: Columbia University
Runji Gao: New York University
Rachel Tang: New York University
Madalina Vlasceanu: New York University

Nature Climate Change, 2025, vol. 15, issue 1, 44-50

Abstract: Abstract A critical step in tackling climate change involves structural, system-level changes facilitating action. Despite their ubiquity, little is known about how internet search algorithms portray climate change, and how these portrayals impact concern and action. In a sample of 49 countries, we found that nationwide climate concern, but not nation-level climate impact, predicted the emotional arousal caused by climate change Google Image Search outputs, as rated by a naive sample (n = 383). In a follow-up experiment we randomly assigned another sample (n = 899) to receive the climate change image outputs resulting from searches conducted in countries high or low in pre-existing climate concern, and found that participants exposed to images from countries with high pre-existing concern (compared to low) became more concerned about climate change, supportive of climate policy and likely to act pro-environmentally, suggesting a cycle of climate sentiment propagation systemically facilitated by internet search algorithms. We discuss the implications of these findings for climate action interventions.

Date: 2025
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DOI: 10.1038/s41558-024-02178-w

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