Climate change impacts are not only leading to physical consequences in terms of direct threats to life, infrastructure, and the natural environment, but also have profound social implications and threaten to widen existing inequalities.
Climate change-related inequalities in psychosocial wellbeing, are relatively difficult to analyse directly because they are typically subjective experiences and feelings at the individual level. Recent developments in social data science and machine learning techniques, mean the disproportionate effect of climate change on different vulnerable groups can be measured and tracked using emerging sources of digital data. These new data sources contain patterns of various human behaviours in vulnerable people, which can be utilised to infer individual differences in psychosocial wellbeing. This data makes it feasible to understand how and to what extent climate change exacerbates social inequalities by affecting psychosocial wellbeing, and what protective factors and support requirements are needed. It also provides a new lens to study and address climate change and psychosocial wellbeing inequality within a uniform data environment and technique framework.
This project aims to build a cross-national network of multidisciplinary researchers between the UK and the Korea Advanced Institute of Science and Technology (KAIST) in South Korea, to investigate the effect of climate change on psychosocial wellbeing inequalities with emerging sources of digital data. Each side will contribute to this network with complementary expertise in climate adaption, risk communication, health inequality, forecasting, data mining and machine learning.