Problem
Research questions and friction points this paper is trying to address.
flood-related wellbeing
public discourse
threat appraisal
social-ecological resilience
psychological consequences
Assessing flood-related wellbeing from public discourse in Ireland using large language model as judge, 2012--2025
🤖 AI Summary
This study addresses the unclear mechanisms by which extreme climate events affect socio-psychological well-being. We propose a novel, unobtrusive assessment framework grounded in public discourse, leveraging large language models to construct an inference pipeline that integrates multi-domain sentiment analysis and data mining techniques. From large-scale text corpora, we extract multidimensional well-being indicators under flood exposure in Ireland—specifically threat appraisal, coping efficacy, and institutional trust—to generate a longitudinal dataset spanning 2012 to 2025. Our findings reveal two critical moderating pathways: “appraisal-efficacy” and “social buffering.” Empirical evidence demonstrates that social support resources significantly enhance perceived efficacy and mitigate adversity-induced stress. Ultimately, this work provides a new paradigm for quantifying socio-ecological resilience.
📝 Abstract
Flooding is an environmental hazard that produces social and psychological consequences for exposed individuals, shaping threat appraisal, perceived coping capacity, access to social support, and confidence in institutional response. This paper studies flood-related wellbeing in Ireland from 2012 to 2025 using large-scale, unobtrusive public discourse from Meta Content Library. We develop a bespoke flood-wellbeing instrument organised with three domains: \emph{affective--cognitive distress appraisal}, \emph{diminished perceived efficacy and agency}, and \emph{perceived relational--institutional connectedness}. We then design a flood-wellbeing reasoning pipeline with large language models to extract multi-indicator, multi-domain flood-wellbeing measures from public discourse at scale. The analysis reveals both stressor activation and social--ecological resilience mediation pathways in Irish flood discourse. Flood stressors directly activate affective--cognitive distress appraisal, diminished perceived efficacy and agency, and perceived relational--institutional connectedness. The analysis further identifies two major mediation pathways: an appraisal--efficacy pathway linking flood exposure to threat appraisal, affective burden, uncertainty, and perceived coping capacity; and a social-buffering pathway in which social and institutional protective resources are associated with perceived efficacy and appraisal of flood-related adversity. The paper contributes an unobtrusive discourse-based approach to flood-wellbeing research by introducing a bespoke instrument, identifying activation and mediation pathways in flood discourse, and producing a temporal dataset for studying wellbeing, adaptation, and resilience under recurrent flood exposure.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Large Language Model as Judge
Flood-related Wellbeing Instrument
Reasoning Pipeline
Public Discourse Analysis
Social-Ecological Resilience
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