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Using Google search data to inform global climate change adaptation policy

  • Carla L. Archibald
  • Nathalie Butt
Article

Abstract

The well-being of human societies in many parts of the world is threatened by climate change. While climate change is global, impacts are local and regional, and vulnerability varies widely across communities, countries, and regions. Climate change awareness has been related to how willingly communities adapt to climate change; thus, identifying communities’ awareness could help to gain insights into communities’ willingness to adopt climate change policy. In this study, we use culturomics to analyze big data from Google™ search queries to group countries based on their awareness, potential willingness, and potential capacity to deal with climate change. We demonstrate that culturomics can be used to allocate countries along a typology gradient, ranging from high-risk and high awareness to low-risk and low awareness, to climate change. Furthermore, we identify a positive correlation between countries’ climate vulnerability and awareness of climate change. As the Paris Agreement establishes a global goal to “enhance adaptive capacity, strengthen resilience and reduce vulnerability to climate change,” identifying countries’ potential adaptive capacity to climate impacts is critical. Pairing culturomics insights with climate vulnerability is a novel approach to facilitate international climate change adaptation.

Notes

Acknowledgements

CA is supported through an Australian Postgraduate Award and a top-up scholarship through the ARC Centre of Excellence for Environmental Decisions. NB is supported by ARC Grant DE150101552. The authors would like to thank Dr. Jason Samson for providing climate vulnerability data and Dr. Megan Evans, Blake Alexander Simmons, Felicia Jane Runting, Dr. Morena Mills, and Associate Professor Jonathan Rhodes for reviewing and providing useful comments during the drafting process of the manuscript.

Supplementary material

10584_2018_2289_MOESM1_ESM.docx (6 mb)
ESM 1 (DOCX 6154 kb)
10584_2018_2289_MOESM2_ESM.xlxs (42 kb)
ESM 2 (XLXS 42 kb)

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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.School of Earth and Environmental SciencesThe University of QueenslandSt LuciaAustralia
  2. 2.Australian Research Council Centre of Excellence for Environmental DecisionsThe University of QueenslandSt LuciaAustralia
  3. 3.School of Biological SciencesThe University of QueenslandSt LuciaAustralia

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