Based on fuzzy multi-class support vector machine, a method for detecting microblog spammers is designed. Firstly, a multi-class SVM(support vector machines) is used to construct multi-classifiers, and a training set is re-selected for each type of user's classifier. Then, the constructed training set is used to train the multi-classifier, and five user classifiers are obtained after repeated remediation. Finally, for the non-separable samples of multiple classifiers, fuzzy clustering is used to perform the fuzzy processing. An improved membership function is defined on the optimal classification plane perpendicular to the SVM, and the maximum membership degree is used to reclassify the samples. Experimental results show that this method can solve the problems of mixing and missing points in multi-classification under the premise of ensuring the detection effect of spammers.