The invention provides a short text topic identification method and system, and relates to the technical field of data processing. The method comprises the following steps of S1, obtaining a first corpus set and a second corpus set, wherein the first corpus set is a short text data set to be processed, and the second corpus set is an auxiliary corpus set; S2, obtaining a hidden feature vector based on words on the second corpus set, and constructing a Dirichlet process hybrid model based on the first corpus set; S3, constructing a non-parameter theme model based on the implicit feature vectorand the Dirichlet process hybrid model; S4, performing parameter inference on topic posterior distribution of the non-parameter topic model; S5, inferring and identifying the number of topics in the first corpus set based on the parameters, and obtaining the document-topic distribution and the topic-word distribution in the first corpus set at the same time. According to the method, the Dirichletprocess hybrid model and the implicit feature vector representation of the introduced words are constructed, so that the sparsity problem can be effectively relieved, and the accuracy of short text topic identification is improved.