The impact of climatic factors on negative sentiments: An analysis of human expressions from X platform in Germany
Tareq Al-Ahdal,
Sandra Barman,
Stella Dafka,
Barrak Alahmad,
Till Bärnighausen,
Michael Gertz,
Joacim Rocklöv
Affiliations
Tareq Al-Ahdal
Heidelberg Institute of Global Health (HIGH), Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany; Interdisciplinar Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany
Sandra Barman
Bioeconomy and Health, RISE Research Institutes of Sweden, Göteborg, Sweden
Stella Dafka
Heidelberg Institute of Global Health (HIGH), Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany; Interdisciplinar Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany
Barrak Alahmad
Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
Till Bärnighausen
Heidelberg Institute of Global Health (HIGH), Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
Michael Gertz
Interdisciplinar Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany; Institute of Computer Science, Heidelberg University, Heidelberg, Germany
Joacim Rocklöv
Heidelberg Institute of Global Health (HIGH), Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany; Interdisciplinar Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany; Department of Public Health and Clinical Medicine, Section of Sustainable Health, Umeå University, Umeå, Sweden; Corresponding author
Summary: Expressions in social media can provide a rapid insight into people’s reactions to events, such as periods of climatic stress. This study explored the link between climatic stressors and negative sentiment on the X platform in Germany to inform climate-related health policies and interventions. Natural language processing was used to standardize the text, and a comprehensive approach for sentiment analysis was utilized. We then conducted spatiotemporal modeling fitted using integrated nested laplace approximation (INLA). Our findings indicate that higher and lower level of temperature and precipitation is correlated with an increase and decrease in the relative risk of negative sentiments, respectively. The findings of this study illustrate that human sentiment of distress in social media varies with space and time about exposure to climate stressors. This emotional indicator of human exposure and responses to climate stress indicates potential physical and mental health impacts among the affected populations.
