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    •   BracU IR
    • School of Data and Sciences (SDS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
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    A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations

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    22341041, 20241062, 19301045, 18101603, 18301243_CSE.pdf (1.709Mb)
    Date
    2023-01
    Publisher
    Brac University
    Author
    Maliha, Miftahul Zannat
    Trisha, Ananya Subhra
    Tamzid Khan, Abu Mauze
    Das, Prasoon
    Shakil, Shuhanur Rahman
    Metadata
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    URI
    http://hdl.handle.net/10361/19233
    Abstract
    For 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
    Keywords
    Crypto-currency; Machine learning; Bitcoin; Sentiment analysis; Prediction; Stock Market
     
    LC Subject Headings
    Machine learning; Digital currency
     
    Description
    This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.
     
    Cataloged from PDF version of thesis.
     
    Includes bibliographical references (pages 29-31).
    Department
    Department of Computer Science and Engineering, Brac University
    Type
    Thesis
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering) [1599]

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