期刊
BIOLOGICAL CONSERVATION
卷 233, 期 -, 页码 298-315出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.biocon.2019.01.023
关键词
Social media; Nature conservation; Biodiversity; Spatial analysis; Content analysis; Machine learning; Artificial intelligence
资金
- Kone Foundation
- University of Helsinki
- Helsinki Institute of Sustainability Science (HELSUS)
- Academy of Finland [296524]
- Helsinki Metropolitan Region Urban Research Program
Improved understanding of human-nature interactions is crucial to conservation science and practice, but collecting relevant data remains challenging. Recently, social media have become an increasingly important source of information on human-nature interactions. However, the use of advanced methods for analysing social media is still limited, and social media data are not used to their full potential. In this article, we present available sources of social media data and approaches to mining and analysing these data for conservation science. Specifically, we (i) describe what kind of relevant information can be retrieved from social media platforms, (ii) provide a detailed overview of advanced methods for spatio-temporal, content and network analyses, (iii) exemplify the potential of these approaches for real-world conservation challenges, and (iv) discuss the limitations of social media data analysis in conservation science. Combined with other data sources and carefully considering the biases and ethical issues, social media data can provide a complementary and cost-efficient information source for addressing the grand challenges of biodiversity conservation in the Anthropocene epoch.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据