Mining User’s Opinion Towards the Rising and Falling Trends of the Stock Market: A Hybrid Model

Abstract

Mining users’ opinions towards the rising and falling trends of the stocks may help the management department estimate the risk and make timely decision. Existing methods ignore the effective fusion of domain information and pre-trained language models, hindering mining implicit semantic information. This paper proposes a hybrid method that adopts masked language modeling to obtain a domain-information-enhanced language model. Firstly, it generates an attention-mechanism-oriented masking based on words’ importance, word-level polarity and terminology. Then, the masked words and their corresponding knowledge are predicted to acquire domain-aware language representation. Experimental results on two public financial sentiment analysis datasets show the efficacy of the proposed model.