Abstract: A classifier based on Logistic Regression（LR） is employed to identify comment spams which have flooded in Web forums.Comparative study on performances of LR and Support Vector Machine（SVM） is presented.It is introduced that a relevancy coefficient vector space model named cVSM which is used to express comment archives.Some feature extractive methods are discussed，including Information Gain（IG），Mutual Information（MI），χ² statistic（CHI） and Document Frequency（DF）.The experiments show that：The learn time of LR is less than 1/10 of SVM’s.DF and IG have better performances than MI and CHI.To be compared with vector space model，cVSM has improved comment spam cognitive capability of classifier.