:::

詳目顯示

回上一頁
題名:政府資料開放平臺之PM2.5即時監測資料分析
書刊名:管理資訊計算
作者:劉振隆張愷珉吳芷軒于采玉李彥君黃鈺珊
作者(外文):Liu, Jenn-longChang, Kai-minWu, Chih-hsuanYu, Tsai-yuLi, Yan-jyunHuang, Yu-shan
出版日期:2018
卷期:7:特刊1
頁次:頁1-12
主題關鍵詞:政府資料開放平臺細懸浮微粒OpView社群聆聽平臺PM2.5Government open data platformParticulate matter 2.5Social listening platform
原始連結:連回原系統網址new window
相關次數:
  • 被引用次數被引用次數:期刊(1) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:1
  • 共同引用共同引用:0
  • 點閱點閱:34
近年來各國政府陸續設置及開放整合/即時監測資料來提供產官學研各單位運用與分析之用,以提供有用資訊供各單位相關業務決策之用,因此,有效運用平臺提供之數據庫為資料科學家重要的工作。本研究為探討政府資料開放平臺內相關台灣細懸浮微粒(PM2.5)之資料分析以及PM2.5引起疾病之關聯,包含呼吸系統、心臟血管系統與中樞神經系統相關方面的影響,以及醫生對於PM2.5對身體健康的看法。本研究在PM2.5社群輿情平臺關聯疾病之分析上主要使用到OpView輿情聆聽平臺,OpView為目前國內最大的社群觀測平臺,可從大量資料的社群網路中蒐集各類文章、討論、新聞,並進一步解析不同類型網站及其影響力。
In recent years, governments in the world have gradually established and opened up integrated/immediate monitoring data to provide the uses and analyses for government agencies, academic communities, and research institutes, so as to provide useful information to divisions of government for decision-making of related business. Therefore, the effective application of the database provided by the platform is an important task for data scientists. This study investigates the data analyses of related Taiwan’s Particulate Matter 2.5 (PM2.5) stored in the government open data platform and analyzes the correlation of PM2.5-induced diseases, including the effects of respiratory system, cardiovascular system, central nervous system, and the doctor's perception of PM2.5 for body health. Furthermore, this study mainly uses a social listening platform, named OpView, for the analysis of community opinions related PM2.5 to diseases. The OpView platform is the current largest community listening platform in Taiwan. It can collect articles, discussions, and news from a large amount of data in the social network, and can further analyze different types of websites and their influence.
期刊論文
1.Pope, C. A. III、Ezzati, M.、Dockery, D. W.(2009)。Fine-particulate air pollution and life expectancy in the United States。New England journal of medicine,360(4),376-386。  new window
2.House of Parliamentary(2014)。Social media and big data. Parliament Office of Science and Technology。POSTNOTE,460。  new window
3.Kahle, D.、Wickham, H.(2013)。ggmap: Spatial visualization with ggplot2。The R Journal,5(1),144-161。  new window
研究報告
1.劉紹興(2014)。細懸浮微粒(PM 2.5)流行病學調查研究 (計畫編號:NSC102-EPA-F-003-001)。  延伸查詢new window
圖書
1.楊立偉、邵功新(2016)。社群大數據:網路口碑及輿情分析。前程文化。  延伸查詢new window
2.Codd, E. F.(1990)。The relational model for database management。New York:Addison-Wesley。  new window
其他
1.彰化醫界聯盟(2011)。PM2.5 與健康,http://www.taiwan921.lib.ntu.edu.tw/KKPT/KKE09.pdf。  new window
2.環境資源資料開放平臺(2018)。細懸浮微粒資料(PM2.5),https://opendata.epa.gov.tw/Data/Contents/ATM00625/。  延伸查詢new window
3.Smith, C.(2014)。Social big data: Each social network is using a very different data lens to understand and target users,http://www.businessinsider.com/social-big-data-the-type-of-data-collected-by-socialnetworks-3-2014-3。  new window
4.World Health Organization(2016)。WHO global urban ambient air pollution database,http://www.who.int/phe/health_topics/outdoorair/databases/cities/en/。  new window
 
 
 
 
第一頁 上一頁 下一頁 最後一頁 top
QR Code
QRCODE