Multiclass emotion analyzing method and system facing bilingual microblog text

Abstract

The invention relates to a multiclass emotion analyzing method and a system facing a bilingual microblog text and belongs to the technical field of microblog text emotion analysis. The method comprises the following steps that (1) bilingual dictionary construction: corpus with an emotion inclination of a certain size is first collected, high frequent words with the emotion inclination can be extracted from the corpus, an emotional dictionary is then expanded by using an existing knowledge database and a vocabulary similarity calculating model, and finally network language and emotional signs are added in the emotional dictionary; (2) text pretreatment: the words are divided in a to-be-identified text, stop words are removed, and standardization treatment is conducted on English word shapes; (3) text characteristic space expression: the bilingual emotional dictionary is used for conducting vectorization on the text; (4) an emotional identifying task of the corpus text is realized through a multi emotion class model. The accurate rate and the F1 valve of the method are higher than those of a traditional classification method, and particularly the classification effect of a semi-supervised Gaussian mixture model classification algorithm in a small-scale training set is obviously better than that of the other methods.

Description

technical field [0001] The invention relates to a sentiment analysis method and system, in particular to a multi-type sentiment analysis method and system for bilingual microblog texts, belonging to the technical field of microblog text sentiment analysis. Background technique [0002] With the rise of social media platforms and the widespread use of mobile devices, people have become accustomed to using 140 characters to express their appeals. Publishing Weibo has become an important means for individuals to express their emotions, so it is of great practical significance to analyze the sentiment tendency of Weibo texts. At present, Sina Weibo has become the main carrier of domestic Internet public opinion, and a large number of users interact with information and express emotions through Weibo. The development of an emotion classification system for user microblog texts and then the completion of emotion recognition has important reference significance in the fields of pu...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that the classification granularity of the existing microblog sentiment analysis method is coarse, the quality of the microblog text analysis is not high for the Chinese and English mix and match, and the identification method of the emotional vocabulary is lagging behind. A Chinese-English bilingual sentiment dictionary construction method for microblog corpus, a bilingual dictionary-based microblog multi-category sentiment analysis method and a bilingual microblog text multi-category sentiment analysis system, so as to perform multi-category sentiment analysis on microblog text

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