A Study on Investor Public Opinion Fluctuation Inversion Monitoring Based on Network Information Sentiment Analysis

摘要

In this paper, not only was data mining performed for investors' social networking platforms of micro-blog and Guba, but a method combining pattern matching and machine learning was adopted for sentiment classification and computing. On this basis, an investor network public opinion fluctuation monitoring could be established to monitor and analyze fluctuations and inversion. Furthermore, validity of this model was verified finally.