Difference between revisions of "Stock Prediction using Social Media Analysis"
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| − | By Scott Coyne | + | By [http://reu.mscs.mu.edu/index.php/User:Scoyne Scott Coyne]] |
Mentor Dr. Praveen Madiraju | Mentor Dr. Praveen Madiraju | ||
Revision as of 17:22, 9 June 2017
By Scott Coyne] Mentor Dr. Praveen Madiraju
Goals and Milestones
1) Complete literature survey of similar projects
2) Compile all social media and stock price info into single data-frame
3) determine sentiment of posts and classify them by value
4) create multiple machine learning models to predict stock prices and evaluate each of them
5) calculate weighted scores for users based on their influence and apply that to the model
6) create a high level architecture diagram of the system
7) produce a final project report
Progress
Week 1
- Installed and used python libraries for data manipulation
- Found API's for mining social media and stock data
- Compiled social media and stock data into single database
- Analyzed sentiment of every post to find mean sentiment of stock per day
Week 2
- Found complete lack of correlation between average sentiment and stock price
- Ran into issues with limited data
- Created regression model that analyzes word-counts and tf-idf of daily posts to predict change
- Reached out to StockTwits and will be given partner-level access to their API
