关键词: Title, TextRank算法, 关键句, 情感分类, 语义规则

Abstract: Considering that different sentences have different degrees of importance in judging the sentiment tendency of a document, thus, distinguishing a key sentence and a specific sentence will help improve the performance of the sentiment classification. Meanwhile, taking into account Title and contextual information, a sentiment analysis method SKTT based on Title and weighted TextRank is proposed to achieve effective sentiment analysis. Firstly, the contribution of Title is calculated according to the sentiment weight of the document Title, considering the impact of punctuation and semantic rules on sentiment orientation. Then, according to the idea of weighted TextRank algorithm, an sentiment sentence directed graph is constructed in the document body to extract key sentences. Finally, the sentiment tendency of all key sentences is calculated to achieve sentiment classification. Experimental results across four domains show that the performance of the SKTT method is significantly better than the Baseline method and has high efficiency.

Key words: Title, TextRank algorithm, key sentence, sentiment classification, semantic rules