Social forest functions including recreation are important for increasingly urbanised societies. For effective management of forest recreation areas, monitoring visitor frequencies is crucial. Increasingly, attempts are being made to incorporate recreational use data into National Forest Inventories (NFI), but given the large scale of national assessments, such data is often elusive. In this study we explore the potential of geotagged social media data for assessing visitor frequencies and explore recreational activities through text-based social media data. We analysed data from Twitter, Flickr and Instagram, both at local scale for 10 NFI forest sites, as well as at national scale to assess recreational use. Data availability was significantly correlated between the three platforms, even though absolute counts differed markedly. The model of recreational visitation based on social media data correlated significantly with an existing potential recreational model, indicating that social media data are a valid source of information for recreational use and can be used in future studies to assess recreational potential. Although data availability limits assessments for small areas of forests, large scale assessments using social media are feasible, and provide a potentially more empirically grounded assessment of recreational potential than theoretical models alone. We suggest that future work should aim at integrating social media data into traditional theoretical recreational models as part of a method triangulation, particularly for areas where recreational usage by visitors is high, but population counts are low. However, because social media data are provided by commercial platforms, we believe that more research is needed into harvesting and analysing other forms of content generated by users to decrease the dependency on commercial social media platforms that may or may not be available in the long run, and can be run locally or through central organisations involved in forest and landscape monitoring and observation.

包括娱乐在内的社会森林功能对于日益城市化的社会很重要。为了有效管理森林游憩区，监测游客频率至关重要。越来越多的尝试将娱乐用途数据纳入国家森林清单 (NFI)，但考虑到大规模的国家评估，此类数据往往难以捉摸。在这项研究中，我们探索了地理标记社交媒体数据在评估访问者频率和通过基于文本的社交媒体数据探索娱乐活动方面的潜力。我们分析了来自 Twitter、Flickr 和 Instagram 的数据，在本地范围内针对 10 个 NFI 森林站点，以及在全国范围内评估娱乐用途。尽管绝对计数显着不同，但三个平台之间的数据可用性显着相关。基于社交媒体数据的娱乐访问模型与现有的潜在娱乐模型显着相关，表明社交媒体数据是娱乐用途的有效信息来源，可用于未来的研究以评估娱乐潜力。尽管数据可用性限制了对小面积森林的评估，但使用社交媒体进行大规模评估是可行的，并且与单独的理论模型相比，可以提供更具经验的休闲潜力评估。我们建议未来的工作应该旨在将社交媒体数据整合到传统的理论娱乐模型中，作为方法三角测量的一部分，特别是对于游客娱乐使用率高但人口数量低的地区。然而，