基于BiLSTM的证券市场情绪感知方法

BiLSTM-Based Sentiment Analysis Approach for Securities Market

摘要: 在证券市场中，市场情绪对投资决策的影响日益显著。基于BiLSTM模型，设计了一种证券市场情绪感知方法，通过数据爬取、数据预处理、词向量构建、情绪分类等步骤，实现了情绪感知。实验表明，该方法能有效捕捉投资者情绪倾向，验证了BiLSTM模型在证券市场情绪感知中的有效性，为投资者提供决策参考。

Abstract: In the securities market, market sentiment has an increasingly significant impact on investment decisions. This paper proposes a BiLSTM-based sentiment analysis method for the securities market, which achieves sentiment perception through key steps including data crawling, data preprocessing, word embedding generation, and sentiment classification. Experimental results demonstrate that the method can effectively capture investor sentiment tendencies, validating the effectiveness of the BiLSTM model in securities market sentiment analysis and providing decision support for investors.