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Protocol for spatiotemporal analysis of climate-induced negative sentiment in social media
Tareq Al-Ahdal1, Sandra Barman2, Barrak Alahmad3
1Heidelberg Institute of Global Health, Section for Oral Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany; Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany.
Abstract:
Climate-induced stressors are associated with population-level mental well-being, yet reproducible workflows linking environmental data to social media sentiment remain scarce. Here, we present a protocol for analyzing spatiotemporal associations between climate-induced stressors and negative sentiment from geotagged social media data. We describe steps for preprocessing large-scale geotagged X data, performing multilingual sentiment analysis with Linguistic Inquiry and Word Count (LIWC-22), integrating climate and health indicators, and fitting a Bayesian spatiotemporal Poisson model. This protocol supports analyses of associations across diverse climate stressors and European regions. For complete details on the use and execution of this protocol, please refer to Al-Ahdal et al.1 and Al-Ahdal et al.2.
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