If we can demonstrate that social media accurately captures a population's sentiment, it could be a more affordable, accessible and timely alternative to what are otherwise expensive and logistically challenging surveys. In the case of disease forecasting, if social media posts did indeed serve as a predictive tool for outbreaks, those data could be used in educational campaigns to inform citizens of the risk of an outbreak (due to vaccine exemptions, for example) and ultimately reduce that risk by promoting protective behaviors (such as washing hands, wearing masks, remaining indoors, etc. ).
如果我们能证明社交媒体能准确捕捉公众情绪,相较于昂贵、交通十分不便的调查而言,它就可以成为一种更实惠、可获取和及时的替代方法。如预测疾病时,如果社交媒体数据确实是有效预测疾病爆发的工具,这些数据就可以用来教育公众,告诉他们有疾病爆发的风险(例如疫苗豁免),并最终通过促进保护性措施来减小危害(如吸收、戴口罩、待在室内等)。
All of this illustrates the potential for big data to solve big problems. Los Alamos and other national laboratories that are home to some of the world's largest supercomputers have the computational power augmented by machine learning and data analysis to take this information and shape it into a story that tells us not only about one state or even nation, but the world as a whole. The information is there; now it's time to use it.
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