论文标题
图理论方法是评估自然在全球范围内对人的贡献
A Graph Theory approach to assess nature's contribution to people at a global scale
论文作者
论文摘要
在大规模的文化生态系统服务（CES）评估在海洋生态系统中至关重要，因为它们反映了人类与自然之间的关键身体和认知相互作用。用图理论对社交媒体数据的分析是一种有前途的方法，可以提供有关用户对不同海洋生态系统看法的全球信息。选择了14个区域来说明在社交媒体数据上使用图理论。研究了已知的旨在保护海洋生态系统的关键娱乐，教育和遗产属性的所选领域，以确定用户偏好的可变性。为每个区域提取了Instagram数据（即与照片相关的主题标签），允许对用户最欣赏的CE进行深入评估。使用网络中心度度量对标签进行分析，以识别单词簇，这是传统照片内容分析通常不会捕获的方面。探索了主题标签网络的紧急特性，以表征访客的喜好（例如文化遗产或自然欣赏），活动（例如潜水或远足），首选栖息地和物种（例如森林，海滩，企鹅）和感受（例如，幸福，幸福或放置身份）。 Instagram主题标签上的网络分析允许描述用户在自然区域周围的论述，该区域提供了至关重要的信息，以有效地管理流行的自然空间。
Cultural Ecosystem Services (CES) assessment at large scales is crucial in marine ecosystems as they reflect key physical and cognitive interactions between humans and nature. The analysis of social media data with graph theory is a promising approach to provide global information on users' perceptions for different marine ecosystems. Fourteen areas were selected to illustrate the use of graph theory on social media data. The selected areas, known to protect key recreational, educational and heritage attributes of marine ecosystems, were investigated to identify variability in users' preferences. Instagram data (i.e., hashtags associated to photos) was extracted for each area allowing an in-depth assessment of the CES most appreciated by the users. Hashtags were analysed using network centrality measures to identify clusters of words, aspects not normally captured by traditional photo content analysis. 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.
