Digital windows into nature’s values: A critical review of cultural ecosystem services research with social media data

Understanding how people relate to nature is essential for addressing today’s complex social-ecological challenges. Cultural ecosystem services offer a valuable lens for exploring the non-material dimensions of human–nature relations. In recent years, social media data have reshaped this research field, enabling novel insights but also introducing important challenges. This study systematically reviews and critically analyzes 218 peer-reviewed articles on cultural ecosystem service assessments that use social media data. We examine geographic and biome-specific coverage, platforms and media formats employed, and key methodological developments, including the increasing role of artificial intelligence for automated content analysis. We further investigate how cultural ecosystem services are conceptualized and classified, organizing thematically similar categories from the literature into semantically coherent clusters, thereby highlighting tensions between universal frameworks and context-specific approaches. Despite growing interest and rapid methodological innovation, the field continues to grapple with platform-specific biases, data accessibility limitations, and a lack of coherence in cultural ecosystem services definitions and identification criteria. The continued reliance on a few dominant sources, particularly Flickr, and the prevalence of studies that draw data from only one platform raise concern about representativeness and long-term sustainability. To support future research, we propose a set of considerations aimed at strengthening analytical rigor and cross-study comparability. These include distinguishing between user-expressed and researcher-inferred experiences, differentiating ecosystem services from the benefits the generate, and explicitly addressing the “ecological” and “use” clauses of ecosystem services frameworks. While challenges remain, research in this area holds substantial promise for enabling scalable, near real-time, and nuanced assessments of cultural human–nature relationships.