[Objective] This paper proposes a novelty detection method to identify authorship. [Methods] We built an algorithm combining one-class SVM or multivariate Gaussian algorithm with multi-layer stylistic feature model. Then, we proposed a threshold selection method based on tolerance t. [Results] When the total number of sample characters was greater than 500, the accuracy, recall and F1 values were more than 0.9. Once the number of sample characters reached 2000, the accuracy, recall and F1 values were 0.978, 0.984 and 0.979. [Limitations] The model’s performance with short texts needs to be improved. [Conclusions] The proposed method could effectively address the novelty detection issue facing long text for authorship identification.
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