Text classification and topic mining of intelligent forum comments in university MOOC based on CNN networks

This study conducted an intelligent classification of comments on MOOC forums, categorising texts based on urgency and subject. In emergency level classification, LSTM recurrent neural network is used, and after identifying emergency comments, Bayesian subject mining models and CNN networks are used to perform secondary text classification. In the emergency classification simulation experiment, the RNN-LSTM model proposed in this study has three evaluation indicators: overall accuracy, recall rate, and F1 value, which are 0.91, 0.949, and 0.94, respectively, which are higher than conventional classification methods. In the practical application scenario of text mining, the probability of misjudgement of Bayesian network combined with CNN model is 4%. Research has shown that the MOOC forum intelligent management comment classification method proposed in this study can effectively increase the feedback efficiency of teachers in MOOC forum comment management, and improve the feedback communication effect of teacher-student education communication.