CashTagNN: Using sentiment of tweets with CashTags to predict stock market prices

2016 11th International Conference on Intelligent Systems: Theories and Applications (SITA)(2016)

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摘要
In this paper we discuss a system, CashTagNN, which uses the sentiment and subjectivity scores of tweets that include cashtags of two companies, Apple and Johnson and Johnson, to model stock market movement, and in particular predict opening and closing stock market prices. We demonstrate that by using only sentiment and subjectivity along with a neural network machine learning model we can predict the opening and closing prices of the two companies with high accuracy.
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关键词
CashTagNN,stock market prices prediction,sentiment scores,subjectivity scores,tweets,Apple,Johnson,neural network machine learning model,opening prices,closing prices
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