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dc.contributor.authorCarter, Caymen
dc.date.accessioned2023-04-18T22:05:20Z
dc.date.available2023-04-18T22:05:20Z
dc.date.issued2022-05-12
dc.identifier.urihttp://hdl.handle.net/20.500.12648/8621
dc.description.abstractThis work presents multiple Long Short-Term Memory neural networks used in conjunction with sentiment analysis to predict stock prices over time. Multiple datasets and input features are used on a LSTM model to decipher which features produce the best output predictions and if there is correlation to the sentiment of posts and the rising of a stock. This project uses embedding based sentiment analysis on a dataset collected from Kaggle which includes over one million posts made on the subreddit r/wallstreetbets. This subreddit recently came under fire by the media with the shorting of Gamestop in the stock market. It was theorized that this subreddit was working as a collective to drive up the price of multiple stock, therefore hurting large corporations such as hedge funds that had large short positions on multiple stocks.en_US
dc.language.isoen_USen_US
dc.subjectstock pricesen_US
dc.subjectLSTMen_US
dc.subjectsubredditen_US
dc.subjectstock marketen_US
dc.subjectsocial mediaen_US
dc.subjectRedditen_US
dc.titleStock Price Prediction Using Sentiment Analysis and LSTMen_US
dc.typeMasters Projecten_US
dc.description.versionNAen_US
refterms.dateFOA2023-04-18T22:05:21Z
dc.description.institutionSUNY Polytechnic Instituteen_US
dc.description.departmentDepartment of Computer & Information Scienceen_US
dc.description.degreelevelMSen_US
dc.description.advisorReale, Michael J.
dc.description.advisorConfer, Amos
dc.description.advisorUrban, Christopher
dc.date.semesterSpring 2022en_US


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