Review of Textual Sentiment Research in Financial Markets

[Objective] This paper analyzes and summarizes the current situation of the development of text sentiment in financial markets, and provides reference for subsequent related research. [Coverage] We used “financial market”,“text sentiment analysis”,“text sentiment”and“investor sentiment”as keywords to search on academic platforms such as CNKI, Web of Science and Google Academic, and extended the search for relevant literatures. A total of 115 papers were reviewed. [Methods] We classified the extracted text sentiment according to the type of the source financial text, then introduced the framework of text sentiment analysis, and finally sorted out the relevant research results on the impact of text sentiment on the financial markets. [Results] Text sentiment in financial markets can be divided into information reporting sentiment, news media sentiment and social media sentiment. In the construction of sentiment indicators, dictionary-based methods and machine learning-based methods are widely used. The above three text sentiments have a certain impact on the financial markets. [Limitations] Due to the universality of text analysis methods in various fields, the selected literature on the framework of text sentiment analysis is not entirely focused on the financial markets. [Conclusions] When constructing financial text sentiment indicators, we should choose the appropriate sentiment analysis method according to the text characteristics, research conditions and research objectives. © 2023 Chinese Academy of Sciences. All rights reserved.