Concerning the low accuracy of micro-blog clustering, on the basis of research on the micro-blog data, micro-blog hashtag was used to enhance vector space model, and micro-blog forwarding relationship was used to improve the accuracy of clustering. With the information such as forwarding number, comment number of a micro-blog and information of the user who posted the blog, topic keywords of the clusters were extracted. Clustering results on the experiments of Sina micro-blog dataset show that, compared with k-means algorithm and ICST-WSNB (a short Chinese text incremental clustering algorithm based on weighted semantics and Naive Bayes), the accuracy of the proposed clustering method based on topic labels and forwarding relationship increases by 18.5% and 6.63% respectively; the recall and F-value are also improved. The experimental results show that the proposed clustering algorithm based on micro-blog topic label and forwarding relationship can effectively improve the accuracy of micro-blog clustering, and then get more appropriate topic words.