A study on the impact of investor sentiment on individual stocks based on text mining

This paper investigates the influence of investor sentiment on individual stock prices through text mining. By reviewing relevant theories and literature, we utilized web crawler technology to collect comment data from the Eastmoney Stock Bar, constructing a comprehensive index of investor sentiment and an index of investor sentiment for individual stocks. Employing the VAR model and Granger causality test, we analyzed the correlation and dynamic relationship between investor sentiment and stock price fluctuations. The study found that stocks of different types of financial institutions react differently to investor sentiment, and that investor sentiment significantly affects stock prices. This paper puts forward corresponding policy recommendations, which can help market investors make scientific decisions and promote the healthy development of the market.