Abstract: 【Purpose/significance】This paper analyzes the emotional evolution process of netizens in public health emergencies,and ex⁃plores the factors that affect the emotional fluctuation of netizens and the differences in space-time evolution【. Method/process】Python was used to crawl 315445 pieces of COVID-19 related text data from Micro-blog,and sentiment analysis was performed on the data text based on SnowNLP sentiment analysis tool.The TF-IDF and LDA theme models were used for modeling,and the temporal and spa⁃tial evolution and differences of public opinion in different stages and groups were analyzed【. Result/conclusion】The emotional evolu⁃tion of Internet users showed phased and group differences.Although the overall situation was positive,the rising period of the epidemic
was the period of concentrated outbreak of negative emotions; Among the netizens,the group with lower education level has greater emotional fluctuation,is more vulnerable to the influence of public opinion,and the evolution of public opinion is more polarized; The emotional fluctuation in central big cities is relatively stable,and the negative emotions of netizens in other regions are often caused not by the epidemic itself,but by the negative public opinion caused by the epidemic; Compared with ordinary netizens,influential groups have more serious negative emotions in the stage of public opinion evolution.Emotional evolution presents obvious ripple effect in each stage.It is necessary to formulate effective public opinion guidance policies for different groups in different stages【. Innovation/limita⁃tion】This paper divides the whole corpus into more than 50 small corpora.Very few small corpora have too little text information,which
has certain limitations.