Department of Renewable Marine Resources, Institute of Marine Science (ICM-CSIC), Passeig Marítim de la Barceloneta, n° 37-49, 08003, Barcelona, Spain.
Department of Marine Ecosystem Dynamics, IMEDEA (CSIC-UIB), Miquel Marqués 21, 07190, Esporles, Spain.
Sci Rep. 2021 Apr 27;11(1):9118. doi: 10.1038/s41598-021-88745-z.
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 people.
社交媒体数据的图论应用是一种很有前途的方法，可以识别人类与自然之间复杂的物理和认知相互作用的新兴特性。为了在全球范围内检验这种方法的有效性，从十四个自然区域选择了 Instagram 帖子，以分析这些区域的新兴话语。这十四个地区以提供关键的娱乐、教育和遗产价值而闻名，利用不同的中心性指标对其进行了研究，以检验图论识别生态系统社会感知和使用变化的能力。使用网络中心性度量标准对 Instagram 数据（即与照片相关联的标签）进行了分析，以描述社交媒体用户发布的标签之间连接的特性。通过这种方法，探索了标签网络的新兴特性，以描述游客的偏好（例如，文化遗产或自然欣赏）、活动（例如，潜水或徒步旅行）、首选栖息地和物种（例如，森林、海滩、企鹅）以及感受（例如，幸福或地方身份）。对 Instagram 标签的网络分析可以划定用户对自然区域的讨论范围，这为有效管理受人们欢迎的自然空间提供了关键信息。
