A big-data analysis of human-nature relations in newspaper coverage
Studying human-nature relations in large socio-ecological systems is vital for sustainability; however, it is challenging. Big-data analyses provide a new opportunity to carry out large-scale studies. To explore this opportunity, we examined 25,019 newspaper articles related to nature in 13 countries in Asia using machine learning techniques. The results revealed opportunities and challenges in shaping sustainable human-nature relations, which included the following: many human-nature relations might not yet be captured in literature; cultural ecosystem services might help increase the public's interests in sustainability; regional context matters; and the public might have lower interest in people's positive contributions to nature compared to other human-nature relations. The diversity of topics identified suggests that multiple conceptual frameworks, including ecosystem services, nature's contributions to people, ecological footprint, and social-ecological systems, are needed. This result highlights the need for pluralistic frameworks to comprehensively examine human-nature relations. Overall, the study demonstrates that big-data applications support the analysis of diverse and complex human-nature systems that could help advance the field forward.
Volume / Issue
Start / End Page
International Standard Serial Number (ISSN)
Digital Object Identifier (DOI)