%0 Journal Article %T Research on the Transfer Rules of Internet Users’ Negative Emotional State in Financial Public Opinion %A Lei Li %J Open Journal of Business and Management %P 282-301 %@ 2329-3292 %D 2020 %I Scientific Research Publishing %R 10.4236/ojbm.2020.81017 %X As the rapid development of internet and the booming of financial market in China, the study of extracting the emotional state of netizens from financial public opinions and using it for quantitative investment analysis has drawn a lot of attention. Because of the limitation of datasets scale, quantitative investment analysis based on financial public opinion has some unsolved problems in the research of financial analysis, such as the results cannot predict the stock price in real stock markets. Based on the long-short-term memory network in deep learning, the proposes study combined with the theory of herding effect in behavioral finance, this paper designs an emotional classification model for netizens’ comments on social media, interpret emotional state transaction of netizens through sentiment analysis, forming an investor’s emotional states’ transfer model, and incorporating the emotional states as a factor into the stock price-forecasting model at last. The results show that the investor’s emotional states have a significant impact on stock price volatility. This stock price forecasting method based on sentiment analysis also provides a new technical path for quantitative investment analysis in the financial market. %K Financial Public Opinion %K Netizen %K Negative Emotional State %K Transfer Rule %U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=97636