Public Opinion Analysis and Guidance under Epidemic Situation

During the period of epidemic prevention and control, the spread of negative and false information of public opinion may affect the prevention and control work, and even affect the image of individuals, enterprises, units and the country, so the prevention and control of public opinion is of great significance. Using big data analysis methods, we can detect public opinion under the background of the epidemic more quickly and accurately, so as to guide the bad public opinion in time. This paper summarizes the specific steps and analysis methods of network public opinion monitoring for big data, gives some hot events of epidemic situation, and introduces automatic rumor recognition. The effect of automatic rumor recognition varies with the data set, and the accuracy rate of epidemic rumor recognition based on BERT model has reached 86.7
^%
. This paper also analyzes the psychological characteristics of different groups of Internet users during the epidemic period, and puts forward overall suggestions for the public opinion control of emergencies in the epidemic.