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http://dx.doi.org/10.9723/jksiis.2018.23.3.013

A Study on Text Mining Methods to Analyze Civil Complaints: Structured Association Analysis  

Kim, HyunJong (동아대학교 경영정보학과)
Lee, TaiHun (동아대학교 산학협력단)
Ryu, SeungEui (동아대학교 경영정보학과)
Kim, NaRang (동아대학교 경영정보학과)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.23, no.3, 2018 , pp. 13-24 More about this Journal
Abstract
For government and public institutions, civil complaints containing direct requirements of citizens can be utilized as important data in developing policies. However, it is difficult to draw accurate requirements using text mining methods since the nature of the complaint text is unstructured. In this study, a new method is proposed that draws the exact requirements of citizens, improving the previous text mining in analyzing the data of civil complaints. The new text-mining method is based on the principle of Co-Occurrences Structure Map, and it is structured by two-step association analysis, so that it consists of the first-order related word and a second-order related word based on the core subject word. For the analysis, 3,004 cases posted on the electronic bulletin board of Busan City for the year 2016 are used. This study's academic contribution suggests a method deriving the requirements of citizens from the civil affairs data. As a practical contribution, it also enables policy development using civil service data.
Keywords
Text Mining; Structured Association Analysis; Civil Complaints; Complaint Analysis;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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