TY - EJOU AU - Zhang, Yixian AU - Cheng, Jieren AU - Yang, Yifan AU - Li, Haocheng AU - Zheng, Xinyi AU - Chen, Xi AU - Liu, Boyi AU - Ren, Tenglong AU - Xiong, Naixue TI - COVID-19 Public Opinion and Emotion Monitoring System Based on Time Series Thermal New Word Mining T2 - Computers, Materials \& Continua PY - 2020 VL - 64 IS - 3 SN - 1546-2226 AB - With the spread and development of new epidemics, it is of great reference value to identify the changing trends of epidemics in public emotions. We designed and implemented the COVID-19 public opinion monitoring system based on time series thermal new word mining. A new word structure discovery scheme based on the timing explosion of network topics and a Chinese sentiment analysis method for the COVID-19 public opinion environment are proposed. Establish a “Scrapy-Redis-Bloomfilter” distributed crawler framework to collect data. The system can judge the positive and negative emotions of the reviewer based on the comments, and can also reflect the depth of the seven emotions such as Hopeful, Happy, and Depressed. Finally, we improved the sentiment discriminant model of this system and compared the sentiment discriminant error of COVID-19 related comments with the Jiagu deep learning model. The results show that our model has better generalization ability and smaller discriminant error. We designed a large data visualization screen, which can clearly show the trend of public emotions, the proportion of various emotion categories, keywords, hot topics, etc., and fully and intuitively reflect the development of public opinion. KW - COVID-19 KW - public opinion monitoring KW - data mining KW - Chinese sentiment analysis KW - data visualization DO - 10.32604/cmc.2020.011316