Application of an emotion discriminant analysis system in the management of automobile brand

Abstract

Brand public opinion management involves text,voice and other natural language processing,such as mining the emotions and views of the text and quantifies it.The quantification of emotion in natural language is the emotion discriminant analysis.Considering the disadvantage in the traditional sentiment analysis that based on emotional dictionary and supervision model based sentiment analysis system,a new sentiment analysis system was proposed,and combined with the Naive Bayesian classification algorithm,the accuracy of sentiment analysis was improved,and the ability of quantitative analysis of emotional strength was enhanced.The sentiment discrimination accuracy of the proposed text sentiment analysis engine is higher than that of the common analysis method,and there is no decent of accuracy in out-ofsample texts from different industries.

Keywords

• sentiment analysis;supervised model;naive Bayes;natural language processing