基于浅层篇章结构的评论文倾向性分析

汉语评论文的特点使得可以利用情感主题句表示其浅层篇章结构,该文由此提出一种基于浅层篇章结构的评论文倾向性分析方法。该方法采用基于n元词语匹配的方法识别主题,通过对比与主题的语义相似度大小和进行主客观分类抽取出候选主题情感句,计算其中相似度最高的若干个句子的倾向性,将其平均值作为评论文的整体倾向性。基于浅层篇章结构的评论文倾向性分析方法避免了进行完全篇章结构分析,排除了与主题无关的主观性信息,实验结果表明,该方法准确率较高,切实可行。

Sentiment Polarity Analysis of Reviews Based on Shallow Text Structure

We put forward an approach to recognizing sentiment polarity in Chinese reviews based on the shallow text structure that is represented by topic sentiment sentences. Considering the features of reviews, we identify the topic of a review using an n-gram matching approach. To extract topic sentiment sentences, we compute the semantic similarity of a candidate sentence and the ascertained topic, and meanwhile determine whether the sentence is subjective. A certain number of these sentences are selected as representatives according to their semantic similarity value with relation to the topic. The average value of the representative topic sentiment sentences is calculated and regarded as the sentiment polarity of a review. Experiment result shows that the proposed method is feasible and can achieve relatively high precision.
Key wordsshallow text structure; topic sentiment sentence; review; sentiment orientation analysis; sentiment