Public interest in biodiversity and climate change: A comparative culturomics study of China and the UK - Ting Tong; Magdalena Lenda; Uri Roll; Li Li (PLoS ONE, 2026)
Understanding how the public engages with biodiversity loss and climate change is critical for designing effective environmental policies and conservation strategies. Here we applied a conservation culturomics approach to compare public interest in biodiversity and climate change across China and the United Kingdom, two major environmental actors with distinct governance models and cultural contexts. Using search volume data from the Baidu Index and Google Trends between 2011 and 2022, we identified peak periods of search interest in both countries. We then analysed associated news content during peak and non-peak periods using grounded theory and thematic coding to uncover the dominant drivers of public attention. Our findings reveal a stark contrast between sources of public engagement. In China, the public interest is predominantly state-driven, with peaks aligned with government-led campaigns and international events. Themes, such as domestic governance and ecological civilisation, were the most significant. In the UK, civil society, scientific discourse, and environmental activism act as the key catalysts in shaping public engagement. These differences reflect greater variations in political structures, media ecosystems, and cultural values. Our results highlight the need for context-sensitive communication strategies. By linking digital behaviour with media discourse we offer new insights into public environmental engagement. Our findings further suggest that enhancing bottom-up participation and diversifying environmental narratives in China could foster greater public ownership of conservation efforts, whereas in the UK maintaining inclusive and coherent narratives is essential. However, limitations such as platform algorithms should be considered when interpreting these cross-country comparisons, as they may affect the comparability of search data between Baidu Index and Google Trends.