Exploring, clarifying and satisfying the needs of consumers is the key factor to improve the quality of express logistics service. Taking the text data of online comments on Cainiao platform as the crawler data source and based on the 65 000 pieces of data obtained, this paper uses TFIDF algorithm, word cloud map, semantic network association analysis, LDA topic model and other text quantitative analysis to construct the sentiment dictionary and carry out the text emotion assignment and analysis. It is found that timeliness, reasonable price, quality of service and functionality of application platform are the key factors that make consumers have negative emotional tendency towards the service quality of express logistics. In order to improve consumers’ evaluation of express logistics service quality, it is necessary to pay attention to improving the timeliness of logistics supply chain, improving the rationality of logistics price system, improving the quality of logistics service, and optimizing the functionality of logistics application platform.