A Method of Sentiment Polarity Identification in Financial News using Deep Learning

摘要

In this research, sentiment polarity identification model for finance is developed using financial and economic corpus and deep learning. Specifically, “Japanese Economy Watchers Survey” is used for the corpus and our model accuracy is high. Then the model is applied to evaluate news sentiment for predicting stock return. Our results confirmed that our model captures more news sentiment compared to using common polarity dictionary.