Human-nature interactions through a digital prism: Heterogeneity in user socio-demographics and content across social media platforms

• We comparatively analyze nature-related content across 13 social media platforms. • We explore representation and measurement biases in texts and photographs. • The focus is on nature experiences at Ramat Hanadiv Nature Park in Israel. • Mixed evidence on mitigating biases by integrating data from multiple platforms. • Texts better reflect visitor preferences for park attractions than visual content. User-generated content from social media platforms offers valuable insights into human-nature interactions, yet research frequently relies on data from only one or a few social media platforms. This limitation raises concerns about representation and measurement biases, especially as different platforms vary in user demographics, type of supported media, and content-sharing norms. To address these gaps, we conducted a comparative analysis of user-generated content related to nature experiences across 13 social media platforms, using Ramat Hanadiv nature park in Israel as a case study. We analyzed platform-specific socio-demographic characteristics, including users’ geographic origin, gender, and language, and evaluated differences in textual and visual content shared on each platform. Results were cross-validated against on-site survey data to assess whether combining data from multiple sources could reduce socio-demographic and content-related biases and whether textual, visual, or combined data more accurately reflects visitor preferences. Our findings reveal substantial variability across platforms. While data integration yielded a more balanced demographic representation, the combined content did not uniformly improve alignment with survey data. Textual content analysis offered closer alignment with survey responses, suggesting that it may more accurately capture visitors’ preferences than visual content alone. This study advances social media-based environmental research by showing that accounting for platform and content-type differences is essential for extracting reliable insights to guide environmental management and conservation planning.