| Title |
Mapping the COVID-19 Issues from an Urban Perspective in South Korea - Text Mining Analysis Focused on Newspaper Articles |
| Authors |
김은정(Kim, Eun Jung) ; 심혜민(Sim, Hye Min) ; 원재웅(Won, Jaewoong) ; 강범준(Kang, Bumjoon) |
| DOI |
https://doi.org/10.38195/judik.2020.12.21.6.163 |
| Keywords |
코로나19; 도시공간; 텍스트마이닝; 워드클라우드; 의미연결망 분석 COVID-19; Urban Space; Text Mining; Word Clouds; Semantic Network Analysis |
| Abstract |
The purpose of this study is to review the issue trend on the COVID-19 outbreak in South Korea, from an urban perspective using newspaper article data. This study uses articles from 47 media companies, and the search period was set to 28 weeks from January 20 to August 2, 2020. The COVID-19 pandemic was divided into three phases: emergence phases, diffusion phase, and daily-life distancing phase. We used a big data analysis service, and searched for ‘Corona’ and ‘City’ as keywords. Results of the study were as follows. First, keywords such as ‘China’, ‘virus’, ‘new type’, and ‘Wuhan’ were mentioned a lot in the emergence phase. Keywords such as ‘confirmed patient’ and ‘Daegu’ were appeared most frequently in the diffusion phase, while keywords such as ‘business’, ‘industry’, ‘new deal’, and ‘tourism’ were mentioned frequently in the daily-life distancing phase. Second, the frequency proportion of keywords was significantly different among three phases. Third, word clouds and semantic network analysis showed that the keywords such as ‘planning’, ‘housing’, and ‘space’ began to appear in the daily-life distancing phase. This study can give an idea to urban research and policies in a preparation of COVID-19. |