The use of Graph Theory on social media data is a promising approach to identify emergent properties of the complex physical and cognitive interactions that occur between humans and nature. To test the effectivity of this approach at global scales, Instagram posts from fourteen natural areas were selected to analyse the emergent discourse around these areas. The fourteen areas, known to provide key recreational, educational and heritage values, were investigated with different centrality metrics to test the ability of Graph Theory to identify variability in ecosystem social perceptions and use. Instagram data (i.e., hashtags associated to photos) was analysed with network centrality measures to characterise properties of the connections between words posted by social media users. With this approach, the emergent properties of networks of hashtags were explored to characterise visitors’ preferences (e.g., cultural heritage or nature appreciation), activities (e.g., diving or hiking), preferred habitats and species (e.g., forest, beach, penguins), and feelings (e.g., happiness or place identity). Network analysis on Instagram hashtags allowed delineating the users’ discourse around a natural area, which provides crucial information for effective management of popular natural spaces for peopleThis work is a product of ECOMAR research network (Evaluation and monitoring of marine ecosystem services in Iberoamerica; project number 417RT0528, funded by CYTED). Three co-authors were funded by H2020-Marie Skłodowska-Curie Action during the conduction of this work: SdJ, funded by MSCA-IF-2016 (ref. 743545); AOA, funded by MSCA-IF-2016 (ref. 746361); ARF, funded by MSCA-IF-2014 (ref. 655475)S
