An estimation of emotional polarity for simple sentence using BERT and its effectiveness

Abstract

In recent years, researches on natural language processing are progressing rapidly, and many companies and research institutes are proposing new machine learning models. As for a popular machine learning model in natural language processing Word2Vec by Google Inc. has been used as a mainstream model. On the other hand, BERT by Google AI Language is attracting attention now. In this study, firstly, a method of emotional polarity estimation using BERT is proposed and applied to simple sentences of newspapers. Next, the estimation results are compared with those by the emotional estimation method using semantic analysis without machine learning which the authors already proposed. Finally, this paper shows that the newly proposed method using BERT is superior to our previous method through discussion of the comparison.