Abstract: Online reviews play an important role in customer relationship management, product marketing and other aspects. Effectively using online reviews to analyze user satisfaction is crucial for enterprises to improve their services and products. The variable design of traditional satisfaction analysis methods often relies on expert advice and seldom considers the asymmetric influence of positive and negative attributes. To solve these problems, this paper utilizes opinion mining technology to explore the features of customers online reviews and calculate services quality scores. Besides, PRCA technology is adopted to quantify the positive and negative influences of service attributes, and classify service attributes to Kano categories. Then, the characteristics of the different brand customer satisfaction under different granularity are analyzed, and the priority order of different customers' attributes is given. Finally, this paper mines five common attributes from coffee reviews. The experimental results show that different attributes have asymmetric effects on satisfaction and the influencing factors of customer satisfaction under different granularity have different characteristics. The corresponding refined enterprise management strategy is given. 

Key words: online review, fine-grained opinion mining, Kano model, satisfaction analysis, penalty- reward contrast analysis