토픽모델링을 이용한 서울특별시 응답소 민원데이터 분석

Analysis of Civil Complaint Data at Seoul Metropolitan Government Response Center using Topic Modeling

초록

This study analyzed the contents of complaints in the Seoul Metropolitan Government using potential Latent Dirichlet Allocation (LDA) in topic modeling. For this purpose, we collected and analyzed the complaint cases disclosed in the respondent sites during the period from August 7, 2020 to December 31, 2022. As a result of the analysis, we empirically found that the content of complaints in Seoul has changed over time. In 2020, during the outbreak and spread of COVID-19, corona-related complaints such as quarantine issues and distancing policies appeared. Among transportation-related complaints, there were complaints related to public transportation, such as service, buses, and management, as well as complaints related to housing and urban planning. In 2021, we can see an increase in housing and construction-related complaints. Among housing-related complaints, the proportion of complaints related to urban redevelopment and reconstruction has increased. In addition, complaints in various fields such as environment, living, and transportation have been received through the response center. In 2022, we saw an increase in quarantine-related complaints and voucher-related complaints. We also saw an increase in housing and reconstruction-related complaints. We also saw an increase in quarantine-related complaints during this period.

키워드

민원분류; 응답소; 토픽 모델; LDA 모형; Civil service classification; Seoul Metropolitan Government Response Center; Topic Modeling; LDA Model
제목
토픽모델링을 이용한 서울특별시 응답소 민원데이터 분석
제목 (타언어)
Analysis of Civil Complaint Data at Seoul Metropolitan Government Response Center using Topic Modeling
저자
배광빈; 김강민
DOI
10.24210/kapm.2023.37.3.011
발행일
2023-09
저널명
한국공공관리학보
권
37
호
3
페이지
249 ~ 265