In this paper we propose a quantitative model to study user satisfaction level in online video streaming, which features great variety across video access sessions under the impact of network conditions and user-specific factors. By applying survival analysis to video session duration ratio, which in our study is regarded to be a measure of user satisfaction level, we find user satisfaction is not only related to network QoS factors, such as buffer time and buffer count, but also susceptible to the users' inclination to the contents of videos. Based on Cox regression model, we analyze the quantitative relationship between user satisfaction level in video streaming and several predictor variables such as buffer count rate, buffer time rate and video popularity degree. Experimental results prove that the model can accurately evaluate user satisfaction levels of our test video access sessions with high probability.