Named Entity Recognition (NER) is an important basis for natural language processing. With the rapid development of neural networks, various methods of deep learning have been pervasively applied to text processing. By introducing the self-attention mechanism, as well as combined with deep learning method, a self-attention-based bidirectional long-term and short-term memory conditional random field (SelfAtt-BiLSTM-CRF) method has been proposed to identify entities in microblogs. By utilizing the self-attention mechanism to obtain the dependency between words, this method helps to further improve the recognition ability of the model. Experiments show that the method proposed in this paper has achieved a satisfying recognition effect.