id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-298362-j3fe0qu2	Chen, Jiaoyan	Forecasting smog-related health hazard based on social media and physical sensor	2017-03-31		.txt	text/plain	6231	317	57	We then propose a predictive analytic approach that utilizes both social media and physical sensor data to forecast the next day smog-related health hazard. We then propose a predictive analytic approach that utilizes both social media and physical sensor data to forecast the next day smog-related health hazard. To the best of our knowledge, our research is the first study to systematically model and analyze real-world social media and physical sensor data for smog-related health hazard forecasting. Second, a health hazard prediction model is built using records of public health index, smog severity index, social network diffusion factor and physical observation, and is further utilized to forecast smog-related health hazards. As Fig. 3 shows, we develop an ANN-based prediction model to forecast the next day smog-related health hazard (PHI record) with the inputs including the current and the past air quality observations, meteorology observations and social observations.	./cache/cord-298362-j3fe0qu2.txt	./txt/cord-298362-j3fe0qu2.txt