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.
翻译:以图表理论分析社会媒体数据是一种很有希望的方法,以提供用户对不同海洋生态系统的看法的全球信息。选择了14个地区,以说明在社交媒体数据中使用图表理论的情况;对已知保护海洋生态系统关键的娱乐、教育和遗产属性的选定地区进行了调查,以查明用户喜好的差异;为每个地区提取了Instagram数据(即与照片有关的标签),以便深入评估用户最赞赏的CES;对Hashtags进行了分析,利用网络中心措施,确定文字群,传统照片内容分析通常没有捕捉到的方面;对标签网的突现特性进行了探索,以说明游客的偏好(例如文化遗产或自然欣赏)、活动(例如潜水或打字)、偏好生境和物种(例如森林、海滩、企鹅),以及感觉(例如幸福或地点特性),在Instagram标签上进行了网络分析,以便查明语言群,而传统照片内容分析通常没有捕捉到的方面;对标签网络的突现特性进行了探索,以说明游客的偏好(例如,文化遗产或自然欣赏)、活动(例如潜水或打),首选生境和物种(例如森林、海滩、企鹅),以及感觉(例如幸福或地点)的网络分析。Instagram网分析,允许在自然使用者对自然资源的空间进行有效管理方面提供关键的空间。