中文摘要：

提出量化情感的概念（评论中的情感值），从用户评论的自然语言文本中得到用户表达的情感值。为了计算评论的量化情感，对评论中的情感词的依存关系进行了研究。给出了情感句的量化情感算法。对量化情感与垃圾评论的关系进行分析，通过直观观察，确定了一系列判别方法。最后本文以量化情感值为指标，建立时间序列对网店的评论选行分析，有效地检测了垃圾评论。实验结果证明在检测网店垃圾评论工作中，所提出的方法有良好的检测结果，优于已有的方法.

英文摘要：

A novel concept of quantitative sentiment was proposed, which means the sentiment score of the review. The sentiment score is derived from the natural language text of the review. To calculate the quantitative sentiment, the de- pendency relationships between sentiment words are discussed. A quantitative sentiment algorithm of the sentiment sen- tence is presented. Furthermore, the relationship between quantitative sentiment and sparn reviews is discussed. A series of prediction rules are established through intuitive observation. In the end, the store reviews are analyzed by establishing a time series with quantitative sentiment as indicator. The spare reviews are detected efficiently. Experimental results show that the proposed method has good detection result and outperform existing methods in detecting sore review spam.