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Social media data for conservation science: A methodological overview

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

  1. Kone Foundation
  2. University of Helsinki
  3. Helsinki Institute of Sustainability Science (HELSUS)
  4. Academy of Finland [296524]
  5. Helsinki Metropolitan Region Urban Research Program

向作者/读者索取更多资源

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.

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