An Empirical Study on Software Requirements Classification Method based on Mobile App User Comments

User comments are one of the main ways for IT companies to obtain software evolution requirements. There are two major methods used to classify the software requirements: the traditional user requirements mining method and the user comments requirements mining. The advantage of traditional user requirements mining is that it can communicate with users face to face, but it is time consuming and the results may not be accurate. Therefore, in this paper, we use the user comments requirements mining method to compare the labeling effect of classification methods on the data set of 19,673 comments. The experimental results show that the combination of TF-IDF and logistic regression (LR) works best on the labeled dataset. This experiment combined with word cloud map has excellent effect on obtaining user requirements.