Social media like Twitter and Facebook has significant exploded as the online forum that changes the public discourse in society fast and set trends in topics in a large range. It is well accepted that decision making and individual behaviors can be affected by individual sentiment. Therefore, this situation leads to researchers a question: can the sentiment of public affect some social behaviors like the trend of stock market prices? Followed by the above motivation, in this project, we propose to find a solution for mining the online data from social media database in order to predict the real stock market prices up or down through this ambiguous information by applying the sentiment analysis and data mining algorithms.
- Special Features and Advantages
Applies text mining techniques to create emotional word lists.
Uses the fuzzy set theory to increase the accuracy for mining the hidden quantitative association rules from a large set of ambiguous data.
Applies statistical measure to provide a means for uncertainty representation. Run-on Cloud and Big Data platform to provide near real-time analysis.
Trading Model Development Integrates social media data analysis into high-frequency equities trading models.
Portfolio Optimization Base on the sentiment analysis to re-design the investment portfolios.