Twitter Mood Predicts Stock Market Movement

Download: mood_dataset.zip

In this post, I try to predict the daily up and down movement of stock prices using twitter mood data and machine learning algorithms. Some time ago, I read a paper called “Twitter mood predicts the stock market.” They claimed to be able to predict stock price movement with an accuracy of over 86%. They used 9,853,498 tweets posted by 2.7 million English speaking users in 2008 and showed that general twitter mood could be used to predict the DJIA. 

My initial intention was to reproduce their results. However, their method would have required that I have access to large scale historical twitter data which is not free and probably not cheap. Instead, I found two companies that publish daily mood sentiment for individual stocks with historical data going back a couple of months. You can download here the anonymized dataset I used for IBM and AGN. I have anonymized the dataset for two reasons; I don’t know if it is legal to share this data and secondly, I might decide to use this method for my own financial gain – the results are impressive! 

For the first company that publishes mood data, I  combine the mood data for the previous 2, 5, and 8 days to predict whether a stock price goes up, down or stays flat. The accuracy is around 75% for AGN and 80% for IBM using 8 days of mood data. For the second company that publishes mood data the results where very impressive; around 90%-100% accuracy using just the previous day's mood data for all the stocks I tested. Below are the results summarized in a confusion matrix.

I used a decision tree and 5x cross-validation for all tests.

Company (1) $AGN Confusion Matrix with 2 days worth of mood data   down     flat     up   down 55.1 % 0.0 % 44.9 % 205 flat 33.3 % 0.0 % 66.7 % 3 up 35.9 % 0.0 % 64.1 % 234 198 0 244 442 Note: columns represent predictions, row represent true classes $AGN Confusion Matrix with 5 days worth of mood data   down     flat     up   down 71.7 %  0.0 %  28.3 %  205 flat 66.7 %  0.0 %  33.3 %  3 up 23.7 %  0.0 %  76.3 %  232 204 0 236 440 Note: columns represent predictions, row represent true classes $AGN Confusion Matrix with 8 days worth of mood data   down     flat     up   down 74.9 %  0.0 %  25.1 %  203 flat 0.0 %  0.0 %  100.0 %  3 up 23.5 %  0.4 %  76.1 %  230 206 1 229 436 Note: columns represent predictions, row represent true classes $IBM Confusion Matrix with 8 days worth of mood data   down     flat     up   down 82.8 %  0.0 %  17.2 %  215 flat N/A %  N/A %  N/A %  0 up 20.1 %  0.0 %  79.9 %  249 228 0 236 464 Note: columns represent predictions, row represent true classes Company (2) $AGN Confusion Matrix with 1 day worth of mood data   down     flat     up   down 100.0%  0.0 %  44.9 %  460 flat 0.0 %  100.0 %  0.0 %  46 up 0.0 %  0.0 %  100.0 %  436 460 46 436 942 Note: columns represent predictions, row represent true classes

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