Difference between revisions of "Stock Prediction using Social Media Analysis"
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* Created regression model that analyzes word-counts and tf-idf of daily posts to predict change | * 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 | * Reached out to StockTwits and will be given partner-level access to their API | ||
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| + | '''Week 3''' | ||
| + | * Created Library for regression model so code can be reused in analyzing different stock | ||
| + | * Updated regression model to use past days and ranges of days to predict prices | ||
| + | * Created classification and cluster models using tf-idf | ||
| + | * Still waiting on complete access to StockTwits API | ||
Revision as of 18:39, 15 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
Week 3
- Created Library for regression model so code can be reused in analyzing different stock
- Updated regression model to use past days and ranges of days to predict prices
- Created classification and cluster models using tf-idf
- Still waiting on complete access to StockTwits API
