Abstract: 【Purpose/significance】This study analyzes the generation and time-lag diffusion characteristics of misinformation on social media during public health emergencies, and attempts to reveal the relationship between misinformation and negative emotions so as to support dredging the communication channels for the correct epidemic prevention information.【Method/process】 This research crawled the misinformation about COVID-19 and related Weibo, and used automatic text analysis methods to get the topic distribution of the misinformation; then, we applied Granger causality analysis to show the time-lag diffusion relationship between the misinforma⁃ tion and the related Weibo; finally, we analyzed the relationship among misinformation, related Weibo and negative emotions under dif⁃ ferent topics.【Result/conclusion】It is found that the growth trend of misinformation and related Weibo tend to be the same, but there are differences, or even opposite delay diffusion effect, in the diffusion power of different topics. At the same time, misinformation that leads to negative sentiments will lead to a large-scale public discussion.【Innovation/limitation】This article interprets the evolution of different misinformation topics in public health emergencies from the perspective of time-lag diffusion. The results can provide a new perspective for misinformation analysis and governance. However, our data collection still has limitations. Because the diffusion of mis⁃ information is too widespread to collect all related information.