An Image-based Global Climate Sentiment Index.

As the impacts of climate change on global economic and social systems deepen, identifying and quantifying climate sentiment has become crucial for climate policy design, risk monitoring, and cross-sector governance. To address limitations in existing studies-particularly their reliance on textual data, which introduces strong language dependence and limits cross-country comparability-this study incorporates visual information as the medium for sentiment measurement. Using the Google Images search engine, we collect approximately 3.19 million climate-related images from 19 representative countries over the period 2015-2024. By detecting positive and negative sentiment embedded in visual data, we construct a globally comparable, long-horizon, multi-frequency Climate Sentiment Index. This index transcends linguistic boundaries, substantially improving the accuracy and cross-cultural robustness of sentiment identification. It provides a valuable data foundation and analytical tool for understanding public climate attitudes, tracing risk transmission channels, and analyzing the formation of market expectations, with broad applicability across economic, social, and environmental domains.