Training sample generation is disclosed, Text data, A method for classify public opinion events and relate equipment, in a training sample generation method provided by an embodiment of the present application, At first, that text data is cluster, Because text data is clustered, When a clustering result corresponding to a target category is found, The training samples of the target category can beobtained only by selecting the text data that meet the target category conditions in the corresponding clustering results and then labeling the target category, without analyzing whether the text data in other clusters meet the target category conditions or not. Therefore, the selection range of text data is greatly narrowed, the efficiency of annotation and the accuracy of samples are improved,and the time of annotation text data is shortened. At the same time, it improves the efficiency and accuracy of text data classification and public opinion event classification process.