Informatization Policy (정보화정책)

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Big Data Analysis of Busan Civil Affairs Using the LDA Topic Modeling Technique

LDA 토픽모델링 기법을 활용한 부산시 민원 빅데이터 분석

  • Park, Ju-Seop (Smart Governance Research Center, Dong-A University) ;
  • Lee, Sae-Mi (Smart Governance Research Center, Dong-A University)
  • Received : 2020.02.18
  • Accepted : 2020.04.01
  • Published : 2020.06.30
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Abstract

Local issues that occur in cities typically garner great attention from the public. While local governments strive to resolve these issues, it is often difficult to effectively eliminate them all, which leads to complaints. In tackling these issues, it is imperative for local governments to use big data to identify the nature of complaints, and proactively provide solutions. This study applies the LDA topic modeling technique to research and analyze trends and patterns in complaints filed online. To this end, 9,625 cases of online complaints submitted to the city of Busan from 2015 to 2017 were analyzed, and 20 topics were identified. From these topics, key topics were singled out, and through analysis of quarterly weighting trends, four "hot" topics(Bus stops, Taxi drivers, Praises, and Administrative handling) and four "cold" topics(CCTV installation, Bus routes, Park facilities including parking, and Festivities issues) were highlighted. The study conducted big data analysis for the identification of trends and patterns in civil affairs and makes an academic impact by encouraging follow-up research. Moreover, the text mining technique used for complaint analysis can be used for other projects requiring big data processing.

시민들은 도시 내 발생되고 있는 지역문제에 대해 큰 관심을 가지고 있다. 지방정부는 이러한 지역문제들을 해결하기 위해 노력하고 있지만 시민들의 생활 불편을 줄여주기는 쉽지 않고 이로 인한 시민들의 불만은 민원으로 이어지고 있다. 이를 해소할 수 있는 대안으로 빅데이터 활용을 통해 민원의 특성을 파악하고, 시민들에게 선제적 편의성을 제공하기 위한 노력이 절실하다. 본 논문에서는 LDA 토픽모델링 기법을 활용하여 전자민원의 동향 분석에 관한 연구를 실시한다. 이를 위해 2015~2017년 9,625건의 부산시 전자민원을 대상으로 20개의 민원토픽을 추출하였다. 도출된 민원토픽을 통해 핵심민원을 파악하고, 분기별 비중 추이 분석을 통하여 4개의 Hot 민원(버스정차, 택시기사, 칭찬, 민원처리)과 4개의 Cold 민원(cctv설치, 버스노선, 공원주차장, 축제 불만)을 도출하였다. 본 연구는 민원동향을 파악하기 위해 빅데이터 분석 방법을 제시하였고, 후속 연구를 유발하였다는 학문적 기여도가 있다. 또한 민원분석을 위해 사용한 텍스트마이닝 기법은 빅데이터 처리가 필요한 다른 행정업무에도 활용될 수 있다.

Keywords

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