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Stock prediction using twitter sentiment analysis.
| Content Provider | CiteSeerX |
|---|---|
| Author | Mittal, Anshul Goel, Arpit |
| Abstract | In this paper, we apply sentiment analysis and machine learning principles to find the correlation between ”public sentiment”and ”market sentiment”. We use twitter data to predict public mood and use the predicted mood and previous days ’ DJIA values to predict the stock market movements. In order to test our results, we propose a new cross validationmethodforfinancialdataandobtain75.56%accuracyusingSelfOrganizingFuzzyNeuralNetworks(SOFNN) on the Twitter feeds and DJIA values from the period June 2009 to December 2009. We also implement a naive protfolio management strategy based on our predicted values. Our work is based on Bollen et al’s famous paper which predicted the same with 87 % accuracy. 1. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Period June Twitter Feed Naive Protfolio Management Strategy Djia Value Stock Market Movement Twitter Data Previous Day Djia Value Sentiment Analysis Market Sentiment Predicted Value New Cross Public Sentiment Machine Learning Principle Predicted Mood Public Mood Al Famous Paper |
| Content Type | Text |
