A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations

dc.contributor.advisorHossain, Muhammad Iqbal
dc.contributor.advisorRahman, Rafeed
dc.contributor.authorMaliha, Miftahul Zannat
dc.contributor.authorTrisha, Ananya Subhra
dc.contributor.authorTamzid Khan, Abu Mauze
dc.contributor.authorDas, Prasoon
dc.contributor.authorShakil, Shuhanur Rahman
dc.date.accessioned2023-08-01T06:08:29Z
dc.date.available2023-08-01T06:08:29Z
dc.date.issued2023-01
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 29-31).
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.
dc.description.abstractFor the technological shift, advancing epoch towards cryptocurrency intensified the impactful method. Metaverse can originate the base operation into a diversified level. The extension of digital marketing contributes to blockchain technology more.Our research demonstrates, attested cryptocurrency price evaluation associated with the stock and sentiment. In our research, we have implemented various techniques to predict cryptocurrency prices. Crypto like bitcoin, ethereum and litecoin are the primary focus in this paper. Our research observes the fluctuation into the cryptocurrency prices. In our research procedure, we used the LSTM-GRU hybrid, ARIMA for time series prediction. The research follows sentiment analysis from the twitter scrapped data. The research provides cogent insights of cryptocurrency price prediction fluidity with the stock price and the twitter sentiment on following cryptocurrencies. Additionally, the data merge with the LSTM time series model depicts the cryptocurrency stock market and shows us the relationship between stock price, twitter sentiment and cryptocurrency price pertinence
dc.identifier.otherID: 22341041
dc.identifier.otherID: 20241062
dc.identifier.otherID: 19301045
dc.identifier.otherID: 18101603
dc.identifier.otherID: 18301243
dc.identifier.otherhttps://dspace.bracu.ac.bd/server/api/core/items/c1ba7c87-a3ae-4adf-98d4-e8521d30e3cd
dc.identifier.urihttp://hdl.handle.net/10361/19233
dc.language.isoen
dc.publisherBRAC University
dc.sourceBRAC University Institutional Repository
dc.subjectCrypto-currency
dc.subjectMachine learning
dc.subjectBitcoin
dc.subjectSentiment analysis
dc.subjectPrediction
dc.subjectStock Market
dc.titleA deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations
dc.typeThesis

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