基于层次体系的情感单元表示方法

情感词是情感分析中的基础单元,因此情感词典在情感分析中起着决定性的作用,目前构建情感词典的方法只是用到了单词的语义信息和构词信息,忽略了其所在语境.基于此,对于一些语义未知的词,传统语义方法难以得出其情感权重,而对于一些由于语境变化而产生新用法的词,使用语义方法很难计算出其真实权重.针对这种情况,首先提出了从构字到篇章...

A sentiment unit representation method based on layer hierarchy

Sentiment word is the basic unit in the task of sentiment analysis,so sentiment lexicon plays an important role in sentiment analysis.Currently,the sentiment lexicon building methods only use word formation and semantic information,but ignore the context.Based on this,for some words with unknown semantics,it is difficult for traditional semantic methods to obtain the semantic weight,and for some words that have new usage due to context changes,it is difficult to calculate their true weight using semantic methods.To rectify the problem,a sentiment analysis hierarchy from the word to chapter is proposed.Each layer has a representation method and sentiment value calculation formula corresponding to the upper layer,which subdivides the analysis unit from sentence dimensions into word dimensions.Based on this,this paper proposes an automatic construction method for sentiment lexicon based on the character and the context of sentiment word.This method can calculate the weight of sentiment word by using the public sentiment lexicon,the word formation of sentiment word,and the contextual sentiment tendency of sentiment word,and the obtained result is more accurate.Experiments on the real dataset of social networks show that the sentiment unit constructed in this paper has a 3%improvement in accuracy compared with the previous methods.At the same time,the sentiment unit can be used directly in sentiment analysis tasks and the accuracy of sentiment analysis has a 9%improvement in rule-based sentiment analysis experiments and a 3%improvement in deep learning methods.