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http://dx.doi.org/10.5392/JKCA.2017.17.12.158

Socio-National Issues Detection Modeling based on Domain Knowledge - Focusing on the Issue of Increase in Domestic Inflow Infectious Diseases  

Hwang, Mi-Nyeong (한국과학기술정보연구원 융합기술연구본부)
Lee, Seungwoo (한국과학기술정보연구원 융합기술연구본부)
Publication Information
The Journal of the Korea Contents Association / v.17, no.12, 2017 , pp. 158-168 More about this Journal
Abstract
As the big data technologies advance, there is an increasing interest in systematic methodologies for data-based policy determination especially in the public health area. This study proposes a method to develop an issue detection model through the collaboration with domain experts in order to intelligently detect major socio-national issues on infectious diseases based on data. At first, the factors influencing the 'domestic inflow of foreign infectious diseases' are determined and variables representing the factors are set. Thereafter, by using system dynamics methods, the causal analysis is made to find causal map indicating main influential factors. In this process, an empirical modeling is conducted through collaboration between data analysts and experts in the infectious disease domain. The proposed issue detection approach based on domain knowledges will make it possible to make a decision on policies more efficiently if the detection system is capable of continuos monitoring of the related issues.
Keywords
Horizon Scanning; Issue Monitoring; Modeling; System Dynamics; Infectious Disease Detection;
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