This study investigates emotional patterns in state government disaster guideline documents using keyword-level emotion analysis and TF–IDF based topic modeling, framing disaster policy communication as an emotional–cognitive dual structure, drawing from Situational Crisis Communication Theory. The findings demonstrate a strong negative relationship between fear and neutrality, indicating a functional separation between risk awareness and administrative clarity. Nine topics were identified and organized into clusters centered on operational support, administrative structures, and policy frameworks, while content related to hazards and recovery emerged as a distinct semantic category based on cosine similarity analysis. In the integrated analysis of sentiment and topics, neutral language predominates, reflecting the cognitive dimension of government guidelines, with fear and sadness appearing as secondary but systematically patterned emotions. Fear concentrates in topics addressing hazardous conditions and risk-related content. Emotionally neutral language has traditionally been privileged in public administration, but the findings highlight disaster policy communication shaped by governance objectives that privilege specific emotional orientations aligned with coordination, participation, and risk management. State disaster guidelines function not only as technical instructions but also as structured communicative instruments that operate along a dual cognitive–emotional model, shaping public attention and response.
Building similarity graph...
Analyzing shared references across papers
Loading...
Soyoung Kim
Seoul National University of Science and Technology
WooJe Kim
Seoul National University of Science and Technology
Richard C. Feiock
Office of the Governor
Administrative Sciences
Seoul National University of Science and Technology
Office of the Governor
Building similarity graph...
Analyzing shared references across papers
Loading...
Kim et al. (Thu,) studied this question.
synapsesocial.com/papers/69ec5a6b88ba6daa22dabefc — DOI: https://doi.org/10.3390/admsci16050198