Social media data are transforming sustainability science. However, challenges from restrictions in data accessibility and ethical concerns regarding potential data misuse have threatened this nascent field. Here, we review the literature on the use of social media data in environmental and sustainability research. We find that they can play a novel and irreplaceable role in achieving the UN Sustainable Development Goals by allowing a nuanced understanding of human-nature interactions at scale, observing the dynamics of social-ecological change, and investigating the co-construction of nature values. We reveal threats to data access and highlight scientific responsibility to address trade-offs between research transparency and privacy protection, while promoting inclusivity. This contributes to a wider societal debate of social media data for sustainability science and for the common good.

Blue and green spaces in cities provide essential ecosystem services to their inhabitants, including recreational and experiential opportunities. Their importance became further highlighted during the COVID-19 pandemic as urbanites sought to relieve some of the associated pressure. However, urban ecosystems are threatened by degradation and pollution, but also by other activities, including recreation. In this context, protected areas face the challenge of balancing visitor interests with conservation objectives, particularly in peri-urban areas. Social media provides an opportunity to analyse human activities in such areas. This study investigates spatial and temporal patterns in Instagram photos at three case study sites in Vienna, Lainzer Tiergarten, Lobau, and Nussberg with different protection statuses between 2018 and 2022. Automated content labeling using Google's Cloud Vision API and subsequent classification identified 19 clusters from 54,751 downloaded photos. Seasonal variations were observed, such as the prevalence of Plant and Insect photos in spring and summer, and Landscape content in autumn and winter. The COVID-19 pandemic coincided with and contributed to an increase in user activity, but seasonal trends were unaffected. Site-specific patterns also emerged, with Panoramas dominating in Nussberg, the Riverscape characterizing Lobau, and Woodlands dominating in Lainzer Tiergarten. Our findings demonstrate that automated social media photo content analysis can capture spatial and temporal variations in visitor behavior and landscape preferences, providing valuable insights for targeted visitor management and the establishment of conservation strategies in peri-urban ecosystems. Integrating these analyses with other methods, such as surveys or mobile phone tracking, can provide a more comprehensive understanding of human-environment interactions.