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This study discusses the behavioral financial analysis of investor sentiment on the financial technology platform, and uses text analysis technology to construct investor sentiment indicators. With the rapid development of financial technology, financial technology platform not only provides convenient trading channels, but also enriches market information through technologies such as big data and cloud computing. As an important factor affecting the financial market, investor sentiment has become the focus of research on the financial technology platform. This study collects text data from financial technology platform, uses natural language processing technology to extract investors' emotional tendency, and constructs effective emotional indicators. The research results show that the constructed investor sentiment index can accurately reflect the changes of investor sentiment, and has a certain correlation with the market trend. In addition, the index also shows the forward-looking in market forecasting, which provides a new method for monitoring and forecasting the market sentiment of the financial technology platform. This study not only deepens the understanding of investors' behavior patterns and psychological dynamics, but also provides a new perspective and tool for financial market forecasting and decision-making.
Chenyu He (Fri,) studied this question.