Quantifying Stock Forum Information: A Precise Analysis of Investor Sentiment, Post Characteristics, and Stock Market Volatility

This study uses data from Eastmoney Stock Bar, focusing on the Shanghai Composite Index (SSE Index) in 2024, to examine the impact of investor sentiment, post volume, and total post views on stock market volatility. Investor sentiment is quantified using the SnowNLP algorithm, and a regression model is constructed with robustness checks performed. The results reveal that investor sentiment is significantly positively correlated with the SSE Index's daily trading volume, with positive sentiment driving higher trading activity. In contrast, the volume of posts does not significantly influence trading volume, while the total number of post views shows a positive association with market volatility. This study provides valuable insights for academic research, investment strategy development, and market regulation.