Abstract
빅데이터 분석 기법의 고도화로 다양한 학문에서 광범위한 연구가 이루어지고 있다. 하지만 빅데이터를 활용한 지방정부 정책에 따른 민원 연구는 아직 미흡한 수준이며 특히, 본 연구와 같이 버스민원을 중심으로 연구한 논문은 아직 찾아 볼 수 없다. 따라서 본 연구의 목적은 부산시청의 전자민원에 대한 분석으로 거시적 관점에서 전반적인 민원을 분석하는 것이 아니라 미시적 관점으로 2015년-2017년의 전자민원 데이터 10,421건을 활용하여 민원의 내용 중 가장 큰 부분을 차지하는 버스민원을 분석하고자 한다. 이를 위해 키워드 분석과 텍스트 마이닝을 이용하여 버스와 관련된 주요 키워드들 추출하고 텍스트 네트워크 분석을 통하여 키워드들 간의 강도 및 연관성을 시각화하여 3년 동안 버스와 관련된 주요 키워드 간의 변화와 중요도를 판별한다. 또한 지속적으로 제시되는 주요 민원 키워드와 키워드간의 연관성 분석은 다양한 시각에서 버스와 관련된 민원을 이해 할 수 있다. 본 연구는 민원 발생을 줄이기 위한 대책 마련에 활용될 수 있고 행정의 대응성을 향상시키고 개선점을 파악할 수 있는 사전자료로 활용 할 수 있을 것으로 기대한다.Advancements in big data analysis techniques have enabled a wide range of novel studies to be conducted in various academic fields. However, very little research has employed big data to examine civil complaints, in particular bus-related grievances, in relation to local government policies. Thus, the purpose of this study is to analyze such bus-related civil complaints, which account for the majority of the electronic civil complaints received by Busan City Hall. Utilizing 10,380 cases of electronic civil complaints from 2015 to 2017, the study chose to analyze them from a microscopic rather than a macroscopic viewpoint. The study extracted main keywords related to bus using keyword analysis and text mining. Then, it visualized closeness and correlation among keywords through text network analysis to determine the change and importance among the main keywords related to buses for three years. The continuous correlation analysis among keywords and main civil complaint keywords helped increase our understanding of bus-related complaints from various viewpoints. First, the results revealed that home-work commuting complaints by citizens were the most common. The related keywords were “increase in running buses,” “operating hours,” and “bus route extension,” which had the most correlated keywords. Second, the main civil complaints in 2015 and 2016 were “increases in bus routes and running buses” and “frequency of bus arrival interval” due to home-work commuting. Other issues that were reported included unfriendly bus drivers, the violation of regular operations, and reckless driving during bus service in 2017. Third, correlations among key words, such as “increase in running buses”, “operating hours”, and “home-work commuting” could be analyzed together as civil complaints that require more buses and the adjustment of operating hours to resolve the issues during workers’ commutes. The results of this study are expected to be employed as preliminary data that could assist in the creation of countermeasures to identify areas of improvement, increase the responsiveness of administration, and reduce the number of civil complaints.
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