Preprints
https://doi.org/10.5194/egusphere-2026-3395
https://doi.org/10.5194/egusphere-2026-3395
16 Jun 2026
 | 16 Jun 2026
Status: this preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).

Human Social Sensing for Characterizing Long-Term Water-Related Discourse Dynamics: Implications for Sociohydrological Analysis

Juseong Lee, Wuseong Jeong, Young Gu Her, Jung Jin Kim, Rabin Bhattarai, David J. Yu, and Hanseok Jeong

Abstract. Sociohydrological models seek to represent co-evolving human and water systems. Yet, static assumptions or poorly constrained parameters may limit their capacity to reproduce long-term transitions in societal discourse and policy priorities that shape hydrologic outcomes. To address this gap, we propose and evaluate a human social sensing (HSS) framework that converts long-term public discourse into quantitative, time-resolved proxy indicators associated with water-related discourse dynamics in sociohydrological systems. HSS integrates large-scale text mining with structured manual coding to capture scalable patterns and interpretable context in water-related narratives. We applied this framework to 61 years (1960–2020) of South Korean newspaper coverage, revealing a clear transition from disaster- and development-centered framing to sustained attention on water quality, environmental management, and ecosystem protection, alongside a tonal reorientation from economic development priorities toward environmental sustainability. Text mining identified structural changes in themes and salient terms, including the rising prominence of water-quality and water-resource themes. Meanwhile, manual coding provided an interpretable contextual benchmark for evaluating computational outputs and for identifying periods in which discourse shifts preceded institutional change. Together, the proposed framework generates high-resolution indicators of evolving water-related societal discourse and demonstrates the complementary strengths of computational analysis and human interpretation. By generating empirically derived discourse-level proxy indicators, HSS offers a structured framework for incorporating long-term societal framing and public discourse dynamics into sociohydrological analysis, while preserving interpretive caution about the indirect relationship between media discourse and public perception.

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Juseong Lee, Wuseong Jeong, Young Gu Her, Jung Jin Kim, Rabin Bhattarai, David J. Yu, and Hanseok Jeong

Status: open (until 28 Jul 2026)

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Juseong Lee, Wuseong Jeong, Young Gu Her, Jung Jin Kim, Rabin Bhattarai, David J. Yu, and Hanseok Jeong
Juseong Lee, Wuseong Jeong, Young Gu Her, Jung Jin Kim, Rabin Bhattarai, David J. Yu, and Hanseok Jeong
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Short summary
Public perceptions shape how water is managed, yet remain difficult to quantify over time. We analyzed sixty years of South Korean news coverage, pairing manual interpretation with large-scale text mining to trace shifts in water discourse. Its framing moved from floods, droughts, and infrastructure toward water quality and environmental sustainability. Converting these signals into time-resolved indicators of societal priorities offers a new way to represent human behavior in water management.
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