Financial Sentiment Analysis(FSA): A Survey

With a rapid development in Natural Language Processing (NLP), financial industry meets the demand of analyzing a huge amount of financial text data. Some recent researches have explored Financial Sentiment Analysis (FSA), but there is a lack of a latest review. This paper aims to provide a comprehensive survey on FSA including data source, lexicon-based approach, traditional machine learning approach and recent deep learning approach such as word embedding, CNN, RNN, LSTM and attention mechanism. Our inspirations in future direction like large unsupervised contextual pretraining, hierarchical coarse-to-fine approach, joint learning, transfer learning and possible applications are also discussed.