The invention provides a method for comment text classified extraction based on evolution clustering. The method comprises: step S1, acquiring comment samples, performing word segmentation on commentcontents, and removing stop words; step S2, processing text features, removing feature items which are in low relevance or are irrelevant; step S3, according to a textual emotion vector space model, giving different weights to the text feature items; step S4, using a k-medoids evolution clustering algorithm to cluster the text features; step S5, counting clustering results in each time period, todraw a conclusion. Compared with the prior art, the method for comment text classified extraction based on evolution clustering solves a problem of data sparsity which the text features may face, andreduces calculation complexity. The method has high susceptibility and good stability on abnormal data, and has relatively high clustering precision.