[目的/意义] 跨领域情感分类仍是亟需重点研究的问题之一。[方法/过程] 借助情感无关词，通过谱聚类算法构建源领域与目标领域的跨域情感特征词簇，将谱聚类得到的情感词特征与位置特征、关键词特征、词性特征融入逻辑回归分类算法中，实现基于多特征融合的跨领域情感分类算法；并以用户评论数据进行验证。[结果/结论] 研究结果表明，CDFF(Cross Domain pulse Four Factor)算法可有效实现跨域用户的情感分类，为跨领域情感分类研究提供借鉴。

[Purpose/significance] The sentiment classification is still one of the cross-cutting issues needed to focused on.[Method/process] With the help of emotion unrelated words, by the spectral clustering algorithm, the authors constructed a cross-domain feature words emotion cluster in the source and target areas of the field. The position of the features and characteristics of emotional words, keyword features, and POS features were integrated into the logic of the regression classification algorithm to achieve a cross-cutting emotion classification algorithm based on the multi-feature fusion. [Result/conclusion] Research results show that CDFF (Cross-domain pulse Four Factors) algorithm is effective when the cross-domain user emotion is classified and its provide reference for same study.