2026-10-09T16:46:50Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34041375 2026-10-01T07:58:58Z category_25474 item_type_3 month_year_10_2026

Mapping the Evolution of Sentiment Analysis in Disaster Management: A Bibliometric Analysis Joenathan Prasetya (25088227) Disaster and emergency management Artificial Intelligence Bibliometric studies Disaster management sentiment analysis social media <p dir="ltr">In order to conduct a thorough and transparent bibliometric evaluation of the academic works related to sentiment analysis in crisis settings, the present study employs a quantitative bibliometric methodology based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework. Bibliometrics is an application of mathematical and statistical tools that helps understand the intellectual structure, trajectories, and collaborations in a certain field of research. The findings outline the paradigm shifts occurring in sentiment analysis and disaster research between 2011 and 2026. This evolution has shifted the domain from early static lexicons and basic supervised classifiers to multi-modal deep learning architectures, Large Language Models (LLMs), and dynamic noise-filtering mechanisms capable of converting real-time social streams into actionable situational awareness. Increasingly, this research trajectory is propelled by urgent concerns surrounding climate-induced disasters, where social media serves as a vital digital gauge of public risk perception, panic, and community needs for emergency response planning. Technological advancements have spurred significant interest from the international community, particularly the USA and China, which currently dominate publications in this field. Given this landscape, future research is expected to foster collaboration aimed at developing AI-driven sentiment analysis capable of facilitating rapid and accurate responses. Furthermore, there is an urgent imperative for disaster-prone nations to formulate and enact policy frameworks that prioritize the deployment of systematically integrated, measurable AI-based sentiment tools within official emergency management infrastructure, bridging the gap between social data extraction and real-time operational decision-making.</p> 2026-10-01T07:58:58Z Dataset Dataset 10.6084/m9.figshare.34041375.v1 https://figshare.com/articles/dataset/Mapping_the_Evolution_of_Sentiment_Analysis_in_Disaster_Management_A_Bibliometric_Analysis/34041375 CC BY 4.0