The study aims to address Chinese universities’ image repair strategies after network public opinion events in the field of crisis management; therefore, it takes 43 network public opinion events in Chinese universities as the research object, encodes the official texts issued by universities according to the image restoration strategy, and sums up the image repair strategies commonly used by Chinese universities. Then, natural language processing is used to conduct the sentiment analysis of the online comments obtained. Accordingly, the sentiment index is constructed to evaluate the effect of Chinese universities’ image repair strategies. We find that Chinese universities commonly use the image repair strategy combination of bolstering, provocation, and corrective action; they have not used the apology strategy commonly used in western discourse systems. We also find that the complete information release process has a better image repair effect, particularly in teachers’ lapse and personal safety events. The sentiment index in teachers’ lapse events is the highest and is related to the universities’ corrective actions. The sentiment index in different public opinion hot events is quite different, which may be related to the nature of specific events. In personal safety events, netizens are more satisfied with image repair strategies.