| 학회 |
한국화학공학회 |
| 학술대회 |
2021년 봄 (04/21 ~ 04/23, 부산 BEXCO) |
| 권호 |
27권 1호, p.276 |
| 발표분야 |
공정시스템 |
| 제목 |
Tweet analysis for real-time event detection in climate change corpus |
| 초록 |
Climate change has exerted detrimental impacts on human-being. Along with the increasing of people’s attention on climate change, Twitter is one of the most popular platforms to release public views and opinions, could supply as informative data mining source. To reveal the influential event to public discussion on climate change, we propose a real-time algorithm to monitor tweets and detect the relevant events. Squared prediction error (SPE) and Hotelling T2 are conducted to detect a target event in climate change corpus. Subsequently, an efficient modeling technique are developed for climate change event detection in Twitter. Through this process the discussion of specific climate change events occurring period can be explored.AcknowledgementThis research was supported by a grant from the National Research Foundation of Korea (NRF) funded by the Korean government (MSIT) (No. 2017R1E1A1A03070713), and Korea Ministry of Environment (MOE) as Graduate School specialized in Climate Change. |
| 저자 |
Li Qian1, Jorge Loy-Benitez2, 남기전3, 유창규1
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| 소속 |
1KyungHee Univ., 2Applied Environmental Science, 3Integrated Engineering |
| 키워드 |
공정모사 및 설계 |
| E-Mail |
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| 원문파일 |
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