| 학회 | 한국화학공학회 |
| 학술대회 | 2019년 봄 (04/24 ~ 04/26, 제주국제컨벤션센터) |
| 권호 | 25권 1호, p.171 |
| 발표분야 | 공정시스템(Process Systems Engineering) |
| 제목 | Twitter big data로부터 기후변화에 따른 키워드 추출 (재난/폭염/한파/대기오염) 및 public sentiment analysis |
| 초록 | Extract public sentiment on climate change can be useful on policy decision. Whereas, there are few researches related with the sentiment analysis of negative effects which are along with climate changes. Twitter as a social networking service provides a platform for user to express their opinions and is visible to public, which makes twitter to be a rich resource for academic research. We collected 0.18 million tweets in a week on topic ‘climate change’, ‘air pollution’, ‘heat waves’, ‘floods’, ‘tsunami’, and ‘hurricane’. The periodical trend was found on tweets number of these topic both daily time scale and weekly time scale. The word count plot is implemented to demonstrate the relative important description words of each topic. The sentiment strength detection is carried out for each topic tweets and the relation between each group data is also analyzed. Acknowledgments This work was supported by Korea Ministry of Environment (MOE) as Graduate School specialized in Climate Change. |
| 저자 | Li Qian, 남기전, 허성구, 이가희, 유창규 |
| 소속 | Kyung Hee Univ. |
| 키워드 | 이상진단; 공정 이론 |
| 원문파일 | 초록 보기 |
